Acta Linguistica Asiatica Volume 12, Issue 2, 2022 ACTA LINGUISTICA ASIATICA Volume 12, Issue 2, 2022 Editors: Andrej Bekeš, Nina Golob, Mateja Petrovcic Editorial Board: Alexander Alexiev (Bulgaria), Cao Hongquan (China), Luka Culiberg (Slovenia), Tamara Ditrich (Slovenia), Kristina Hmeljak Sangawa (Slovenia), Hsin Shih-chang (Taiwan), Terry Andrew Joyce (Japan), Jens Karlsson (Sweden), Byoung Yoong Kang (Slovenia), Lin Ming-chang (Taiwan), Wei-lun Lu (Czech Republic), Nagisa Moritoki Škof (Slovenia), Nishina Kikuko (Japan), Sawada Hiroko (Japan), Chikako Shigemori Bucar (Slovenia), Irena Srdanovic (Croatia). Published by: Založba Univerze v Ljubljani (Ljubljana University Press) Issued by: Znanstvena založba Filozofske fakultete Univerze v Ljubljani (Ljubljana University Press, Faculty of Arts). For the publisher: Dr. Gregor Majdic, Rector of the University of Ljubljana For the issuer: Dr. Mojca Schlamberger Brezar, Dean of the Faculty of Arts The journal is licensed under: Creative Commons Attribution-ShareAlike 4.0 International License. ei, ď . i u . ou e o a = . Journal's web page: https://journals.uni-lj.si/ala The journal is published in the scope of Open Journal Systems ISSN: 2232-3317 Abstracting and Indexing Services: Scopus, COBISS, dLib, Directory of Open Access Journals, MLA International Bibliography, Open J-Gate, Google Scholar and ERIH PLUS. [±culminative] [±obligatory] [±tonal] [+tonal] [.culminative] [+obligatory] [.tonal] [+culminative] [+obligatory] PITCH-ACCENT JAPANESE [+tonal] [+culminative] [.obligatory] PITCH-ACCENT SLOVENE [+tonal] [+culminative] [+obligatory] STRESS-ACCENT SLOVENE [.tonal] [+culminative] [+obligatory] Publication is free of charge. Address: University of Ljubljana, Faculty of Arts Department of Asian Studies Aškerceva 2, SI-1000 Ljubljana, Slovenia E-mail: nina.golob@ff.uni-lj.si TABLE OF CONTENTS Foreword ......................................................................................................................... 5 RESEARCH ARTICLES Examples of Corpus Data Visualization: Collocations in Chinese Luboš GAJDOŠ, Elena GAJDOŠOVÁ ................................................................................. 9 Choice Between the Synonymous Pairs of Sutoppu and Teishi: A Case Study on Synonyms of Western Loanwords and Sino-Japanese in Modern Japanese Based on Corpus DENG Qi ......................................................................................................................... 27 The Roman Alphabet Within the Japanese Writing System: Patterns of Usages and Their Significance Hironori NISHI ................................................................................................................ 51 Liushu-based Instruction and Its Effects on the Motivation and Intended Learning Efforts: The Case of Laos Learners of Standard Chinese GUO Qingli, CHEW Fong Peng ....................................................................................... 73 Exceptions vs. Non-exceptions in Sound Changes: Morphological Condition and Frequency LIU Sha ........................................................................................................................... 91 Word-Prosodic Typology: The Traps of Seemingly Similar Japanese and Slovene Nina GOLOB ................................................................................................................. 115 Foreword The linguistic clumsiness of tourists and students might be the price we pay for the linguistic genius we displayed as babies, just as the decrepitude of age in the price we pay for the vigor of youth. Steven Pinker …, however, from the viewpoint of a linguist, it is definitely worth having it all. The articles for the summer 2022 issue mainly involve topics either on second language learning and acquisition or historical language changes and the motives for them. They were carefully picked up from numerous proposals, and we are very grateful to every single contributor and also to the reviewers. This issue opens with the article “Examples of Corpus Data Visualization: Collocations in Chinese” in which Luboš GAJDOŠ and Elena GAJDOŠOVÁ lightheartedly share a highly beneficial practical procedure that can be used in the visualization of language data, especially in language pedagogy. In a very similar manner to the visualization, DENG Qi presents a tangible example from Japanese in the article “Choice Between the Synonymous Pairs of Sutoppu and Teishi: A Case Study on Synonyms of Western Loanwords and Sino-Japanese in Modern Japanese Based on Corpus”, discussing their usage and functions. Yet another article “The Roman Alphabet Within the Japanese Writing System: Patterns of Usages and Their Significance” by Hironori NISHI explores the usages of the Roman alphabet within the present writing system of Japanese, which is, as the author suggests, induced by more and more frequent horizontal writing and the ever-increasing international interaction. The following article was written by GUO Qingli and CHEW Fong Peng and is entitled “Liushu-based Instruction and Its Effects on the Motivation and Intended Learning Efforts: The Case of Laos Learners of Standard Chinese”. It introduces the Liushu-based instruction and examines its effects on the students' motivation and intended learning efforts. LIU Sha wrote the article “Exceptions vs. Non-exceptions in Sound Changes: Morphological Condition and Frequency”, in which the author tries a unique approach to locate factors that explain exceptions in the diphthongization of [i] to [ei] in Mandarin. Last but not least, Nina GOLOB in her article “Word-Prosodic Typology: The Traps of Seemingly Similar Japanese and Slovene” offers a brief review of research trends on prosody, and by introducing the phonetic properties of the two languages and acquisition difficulties by Slovene speakers of Japanese questions the typological similarity between Japanese and Slovene. Editors and Editorial board wish the regular and new readers of the ALA journal a pleasant read full of inspiration, and a rise of new research ideas inspired by these papers. Editors RESEARCH ARTICLES Examples of Corpus Data Visualization: Collocations in Chinese Luboš GAJDOŠ Comenius University in Bratislava, Slovakia lubos.gajdos@uniba.sk Elena GAJDOŠOVÁ Comenius University in Bratislava, Slovakia gajdosova137@uniba.sk Abstract The article aims to show a practical procedure that can be used in the visualization of language data. The paper freely follows our previous articles about the visualization of language data in language pedagogy. We demonstrate how to retrieve language data – in our case from corpora, how to edit data in a spreadsheet program, and then in the last step, how to visualize it on the example of Legal Chinese and partly Legal German. The Javascript library Vis.js via Pyvis is chosen for the visualization of the language data. Keywords: visualization, corpus, Chinese, Javascript library Vis.js, Python Povzetek Namen clanka je predstaviti postopek vizualizacije jezikovnih podatkov. S tem se navezujemo na dosedanje prispevke o vizualizaciji jezikovnih podatkov pri poucevanju jezika. V clanku najprej prikažemo, kako poteka pridobivanje jezikovnih podatkov, kar so v našem primeru korpusi besedil. Nato prikažemo, kako podatke urejamo z orodjem za delo s preglednicami, nazadnje pa se osredotocimo na vizualizacijo podatkov, za kar smo uporabili primer pravne kitajšcine in deloma pravne nemšcine. Za vizualizacijo jezikovnih podatkov smo uporabili dinamicno knjižnico Vis.js in modul Pyvis v Pythonu. Kljucne besede: vizualizacija, korpus, kitajšcina, dinamicna knjižnica Vis.js, Python 1 Introduction Digitized language data can be obtained from several sources. In this article, we chose a corpus as a source of data, though data can also be obtained relatively easily from other sources. A corpus or corpus linguistics brings some benefits when compared to other sources.1 Let us mention a few major benefits: (1) language data are already preprocessed, which means that texts are cleaned, (2) very often texts are tokenized (divided into tokens), (3) texts or tokens are annotated, and (4) corpora are equipped with statistical tools. 1 Corpus linguistics is a well-established part of linguistics. Despite some existing methodology issues, results from corpus linguistics have already proven that some areas of linguistics and language pedagogy are unimaginable without it, such as lexicography or quantitative analyses, just to mention a few. For more details on using the corpus data in language pedagogy, see Petrovcic (2022, pp. 43–47). 2 See Gajdoš (2022b) or Gajdoš (2020) for details. 3 Vis.js is a dynamic, browser-based visualization (JavaScript) library (Vis.js, n.d.). 4 As the data retrieving script is written in Python, Pyvis library should be used to produce Javascript code. Pyvis is designed as a wrapper around the popular Javascript Vis.js library (Pyvis, n.d.). 5 The Hanku corpus is a corpus of the Chinese Language. The zh-law is a subcorpus of legal Chinese (Gajdoš et al., 2016). 6 The COLEGE is a corpus of legal German. See Gajdošová & Gajdoš (2018) for details. 2 Methods As with the data sources, there are many ways to retrieve data from a corpus in general.2 In this chapter, only a basic procedure is introduced. Followed by the preliminary stage of the visualization – data retrieving and data editing, the visualization of data via Vis.js3 library4 is also shown. 2.1 Retrieving data The most conventional way to obtain data from a corpus is to use a built-in corpus manager and, for example, Corpus Query Language (hereafter CQL). As our goal is to find the most “common” collocations in a corpus, there are probably other, more appropriate, or perhaps easier ways to tackle this task. As confirmed by our previous research on the identification of collocations, language data which are obtained directly from the built-in functionalities offered by the NoSketch Engine is advantageous. Both corpora – the subcorpus Zh-law of the Hanku5 corpus and the corpus COLEGE,6 which serve as the data source, use the NoSketch Engine. Because there are many queries for the identification of collocations (only some of the parameters change), it is convenient to use scripting languages. In our case, by retrieving language data from corpora, programming languages like Python7 and the JSON format8 are used, however, the following procedure describes a “manual” way, and it may also be used. 7 Python (version 3) is a programming language, for more information see Python (n.d.). 8 JSON (JavaScript Object Notation) is a lightweight data-interchange format, for more information see JSON (n.d.). 9 Keywords can be selected based on one’s own requirements, e.g. only verbs and nous, as it is in our case (tags VV or NN for Chinese). 10 The CQL query means “searching for all verbs VV or (symbol |) nouns NN”. In the next step, the functionality Node forms sorts tokens by frequency. 11 The most frequent tokens in a corpus do not necessarily create the strongest collocations (measured by the Logdice score). 12 As will be shown in the following chapters, this information is used in the visualization. 13 See Gajdošová (2022) or Gajdoš (2022a) for more information. 14 Abbreviation CSV stands for “Comma-Separated Values”. See CSV (n.d.) for details. 15 See PANDAS (n.d.) for more details. 16 Here it is worth noting that not all spreadsheet programs work properly with the CSV format. Libreoffice Calc has proven to be a good solution in this regard. For more details, see https://www.libreoffice.org/discover/calc/. 17 The side designation may be added manually after obtaining data from a corpus for each side separately. 1. Get keywords (hereafter KWIC)9 from the corpus by using query, e.g. CQL:10 [tag=”VV|NN”], then use node forms functionality, and finally save as .txt format.11 2. Again, based on our previous research, it is advantageous to look for collocations on the right and left sides separately.12 LogDice score is chosen as the basic criterion (the measure of association), and the span is set to 5 to the left and 5 to the right side from KWIC for Chinese, and 10 to the left and 10 to the right for German.13 The results are sorted by node forms and frequency for Chinese, and then lemma for German. The results are saved as a .txt file. As spreadsheet programs may not work properly with .txt formats, it is advisable to simply change the .txt filename extension (a suffix to the name) to .csv.14 2.2 Data editing In this step, the data will get equipped with parameters and will further be formed in the way to best suit the visualization. For our purposes, the Pandas15 library was used to modify the data. The following steps show some manual data modifications. 3. In a spreadsheet program,16 the results from both sides are merged into a single file based on the LogDice score maintaining the side designation.17 4. The previous steps are repeated for all the keywords. The results are then combined into one single .csv file (sorted by the LogDice score). This can be considered as the basis for visualization. Table 1 below shows the results for Legal Chinese. POS tags of KWIC (column POS_kwic) and collocators (POS_item) are added manually at the end of the entire search. According to the requirements, it is possible to add other information that can be obtained from the corpus, such as the author’s gender, period of origin, and others. Table 1: Identified collocations in the corpus Zh-law KWIC Side Item Logdice Corpus POS_kwic POS_item .. LS .. 12,921 Zh-law NN NN .. RS .. 12,914 Zh-law NN NN . RS . 12,856 Zh-law AD VV .. LS .. 12,803 Zh-law NN NR .. RS ... 12,789 Zh-law NN NN .. LS .. 12,483 Zh-law NN NN .. RS .. 12,455 Zh-law NN NN .. RS .. 12,183 Zh-law NN NN .. LS . 12,116 Zh-law NN DT 2.3 Visualization Data visualization can be done in different ways. We here demonstrate only one of the possible ways of using Vis.js – network. The network in the Vis.js library mainly consists of nodes and edges. In our case, the keywords (KWIC) and identified collocators (item) are chosen as the nodes. The following code shows how to create a simple network with three nodes and two connections (edges) as an arrow based on the side (LS). // create an array with nodes var nodes = new vis.DataSet([ { id: "..", label: ".." , shape: "dot", value: 2, group: 1}, { id: "..", label: ".." , shape: "dot", value: 1, group: 2}, { id: "..", label: ".." , shape: "dot", value: 1, group: 3}, ]); // create an array with edges var edges = new vis.DataSet([ { from: "..", to: ".." }, { from: "..", to: ".." }, ]); var edges = [{ from: "..", to: "..", arrows: "from" }, { from: "..", to: "..", arrows: "from" }, ]; As can be seen from the code above, there are many parameters that can be used for nodes and edges. In our visualization, the following parameters are used – shape (dot), value (based on the number of connections/edges to nodes), and group (based on POS tag). Nodes can be dragged via a left mouse click. Figure 1 shows the visualization of a given code. Figure 1: Example of creating a simple network in Vis.js It is possible to create nodes and edges manually, yet with a large amount of data, this procedure is very laborious and time-consuming. For these reasons, it is very convenient to use one of the scripting languages, e.g. Python.18 18 In the first step, the nodes are added within a for loop. In Python with Pandas are used, i.e. “for index, row in df.iterrows():”. For more details, see https://pandas.pydata.org (PANDAS, n.d.). The node ID is then the KWIC or item token. One KWIC or item (any token) is only one node. Edges are connected according to the side. The value of the node (the size) is based on the number of edges to other nodes. The result of the visualization is a .html file that may be displayed in a web browser such as Firefox, Chrome, or any other. Because displaying a large amount of nodes (more than 1000) is computationally intensive, it is a good idea to choose a compromise number of nodes that are meaningful. It is appropriate to take this step when modifying/editing the data. Alternatively, select only some keywords (such as nouns and verbs) and then display them separately. 3 Practical use of visualization Before showing a practical use of the visualization, is necessary to draw attention to the limits of the visualization: • since the tagsets for corpora are different, one must expect a different proportion of POS tags in different corpora • in the case of using the German corpus Colege, it is necessary to consider the relatively small size of the corpus, which may affect the result from the statistical point of view • the visualization is only as relevant as the obtained data • when comparing more languages, it is important to pay attention to genetic and typological differences between them. 3.1 Strongest collocations in Legal Chinese The following example demonstrates possibilities of visualization in the Vis.js library. As already demonstrated, searching for the strongest collocation to one token (KWIC) in Legal Chinese, measured by the Logdice statistical measure, is quite simple. A recursive algorithm is used to search for the strongest collocations in the corpus.19 The following POS tags are excluded from the search: punctuation (PU), time nouns (NT), numbers (CD, OD), sentence particles (SP) and all markers DE., ., . (D.*).20 Table 2 shows only a small portion of the result.21 The whole table has 935 rows. 19 The searching function is called itself until the Logdice value is below a certain value. For more details about recursion, see https://openbookproject.net/thinkcs/python/english3e/recursion.html 20 Needless to say, these restrictions may be set arbitrary, and, in this case, these restrictions are applied to KWIC and collocators (Item). 21 The very first result is particularly interesting. The formula for calculating Logdice shows that the maximum theoretical value is 14, yet this result is higher (Rýchly, 2008). The explanation is in this case quite simple – cooccurrence count (689) of tokens youqi .. (period) túxíng .. (imprisonment; fixed-term imprisonment) is higher than candidate count (619) of ... This phenomenon may be caused by errors in tokenization. Table 2: Strongest collocations in Legal Chinese KWIC Side Item Logdice Corpus POS_kwic POS_item .. LS .. 14,022 Zh-law NN JJ .. RS ... 13,979 Zh-law NR NN ... LS .. 13,979 Zh-law NN NR ... RS ... 13,895 Zh-law NN NN ... LS ... 13,895 Zh-law NN NN .. RS .. 13,894 Zh-law VV NN .. LS .. 13,894 Zh-law NN VV .. LS .. 13,882 Zh-law NN VV .. RS .. 13,882 Zh-law VV NN .. RS .. 13,861 Zh-law JJ NN ... LS . 13,779 Zh-law NN NN . RS ... 13,779 Zh-law NN NN . RS ... 13,733 Zh-law NN NN ... LS . 13,733 Zh-law NN NN ... RS .. 13,601 Zh-law NN NN .. LS .. 13,596 Zh-law NN VV .. RS .. 13,596 Zh-law VV NN .. LS .. 13,484 Zh-law VV VV .. RS .. 13,484 Zh-law VV VV Figure 2: Network of 935 strongest collocations in Legal Chinese As the printed version of the visualization is fairly limited, possibilities of the visualization are demonstrated in the multiple figures. Figure 3 shows the following: • there are nodes (tokens) that make more connections than others, the size of a node reflects this information (mostly blue are nouns and red nodes are verbs) • some parts of speech are more common than others, e.g. blue nodes (nouns)22 • clusters of blue nodes (nouns) and red (verbs) are the most common • arrows point to the collocators (dashed edges to the collocators on the right side, solid-line edges to the collocators on the right side) in the word order. 22 It is worth noting that due to polysemy or conversion (zero derivation), POS tags are not always adequate in a certain collocation in Chinese. Though the above information is also available in the .csv file, we believe that their visualization is more easily readable to a student or in the field of second language acquisition in general. This is also because some information, as shown in Figure 3, can only be retrieved from the table via a search, while in the figure, this information is available by clicking on a node. Also, the figure can be zoomed in or out using the mouse. Figure 3: Zoom in and viewing connection to other tokens After clicking on a node, the pop-up menu would show that the node xíngzhčng .. (administrative) is a noun (NN), which makes collocations with the following tokens in the column: bůmén .. (department), chufá .. (punish), and others. At the same time, the edges are also highlighted. Furthermore, by clicking on the connected node, one can obtain information on the collocators to the connected node as well. The pop-up menu in Vis.js also offers other options, such as a hyperlink directly to examples in the corpus, to the web translator, statistical data, and others. 3.2 Comparison of synonyms There are synonyms in every natural language and one of the difficulties in translating them or in the L2 acquisition is to find their equivalences. Our empirical experiences show that it is appropriate to seek an equivalence, not at the level of words (tokens) but at least at the level of collocations (bigrams, n-grams), as has already been shown by Benická (2017), and others.23 23 For more details about translation issues, see Benická (2017). Let us start with an example of the following three Chinese synonyms: “according to” ŕnzhŕo ..,genjů ..,yizhŕo ... Table 3 shows the first 10 rows. The whole table consists of 193 rows. Table 3: Collocations to given prepositions KWIC Side Item Logdice Corpus POS_kwic POS_item .. RS .. 11,477 Zh-law P NN .. RS . 11,02 Zh-law P NN .. RS .. 11,007 Zh-law P VV .. RS .. 10,958 Zh-law P NN .. RS .. 10,86 Zh-law P JJ .. LS .. 10,809 Zh-law P VV .. RS ... 10,781 Zh-law P NN .. RS .. 10,78 Zh-law P NR .. RS .. 10,769 Zh-law P NN .. RS .. 10,685 Zh-law P NN Figure 4: Collocators to prepositions ŕnzhŕo .., genjů .. and yizhŕo .. As can be seen from Figure 4, these prepositions have mutual collocators, of which some are typical for two prepositions and some even for one preposition only. Let us zoom in to see more details. On the left side of Figure 5, there is a group of genjů .. and ŕnzhŕo ..collocators. The group in the middle are collocators of all three prepositions. The group on the right side are the mutual collocators to ŕnzhŕo .. and yizhŕo ... Figure 5: Mutual collocators of the prepositions 3.3 Comparison of modal verbs in legal texts In the case of translating legal texts, for example, it is very important to find an equivalence in translated languages, in our case for modal verbs. Due to the ongoing research,24 the language pair Chinese – German is chosen as an example. 24 For more details, see Gajdošová (2022). 25 Identifying modal verbs is not a trivial operation, since many modal verbs in Chinese may also be e.g. transitive verbs. There are no specific tags for modal verbs25 in the Chinese corpus, so modal verbs must be selected manually as follows by the CQL query: [word=”.|.|.|..|.|.|..|..|.|..|..|.|..|.|..|.|.|..|..|..|.|.|..” & tag=”VV”] Table 4 below shows the first 10 collocations only. The whole table has 984 rows. Table 4: Collocations of modal verbs KWIC Side Item Logdice Corpus POS_kwic POS_item . LS . 12,846 Zh-law VV AD . LS .. 11,961 Zh-law VV VV . RS . 11,601 Zh-law VV DT . LS .. 11,55 Zh-law VV NN . RS .. 11,415 Zh-law VV VV . LS ... 11,366 Zh-law VV NN . LS . 11,342 Zh-law VV AD .. RS .. 11,134 Zh-law VV NN . LS . 11,068 Zh-law VV AD .. LS . 11,018 Zh-law VV AD As can be seen from Figure 6 below, some modal verbs collocate more often than others. Obrázok, na ktorom je doplnok, vnútri, pestrofarebné, vzduch Automaticky generovaný popis Figure 6: Collocability of modal verbs in Chinese From the list of modal verbs, the token that collocates the most is the verb yingdang .. (should; must), ying . (should), keyi .. (may), dé . (must), and may express deontic modality. The collocability of other verbs is rather limited or they do not collocate at all. Such are yuŕnyě .. (willing to), yuŕn . (willing to), yinggai .. (should), and others. Let us zoom in. It is obvious that the modal verbs yingdang .. (should; must), ying . (should), and dé . (must) have mutual collocators. On the other hand, some modal verbs such as yinggai .. (should) and gai . (should) rarely collocate in Legal Chinese, if at all. Figure 7: Collocability of verbs (from left) yingdang .., ying . and dé . Now let us look at a practical example of using the network in L2 acquisition and select the node bůmén.. (department; division). This node points to the verb yingdang .. (must) and this verb, among others, points to the preposition genjů .. (according to), which further points to the verb xuyŕo .. (a need; to need). Searching for the above tokens in the Zh-law subcorpus brings the results presented in Figure 8. Figure 8: Example of the n-gram in Legal Chinese The visualization may not appear clear enough at first sight. If so, it is advantageous to reduce the number of collocators or modify the parameters of the physical model, e.g. change the value of constants (gravitationalConstant), extend the length of the edges (springLength), etc. though these are rather limitations resulting from the printed version. The .html version solves these problems partially or completely. The downside of the visualization, as the parameters are set in this example (node size based on the number of collocators), is also the inability to display collocation strength based on the Logdice score. An example in this case is the negation bů . (not) which makes the strongest collocation of all modal verbs, in this case with bů dé .. (must not). Besides, the negation bů . can also collocate with other modal verbs in Legal Chinese. Now, let us compare the above situation with the one in Legal German. Taking the same example, we would like to illustrate a different approach to the same problem in two different corpora and languages. This is not an exhaustive analysis of the issue of equivalence in these languages but just a sample of the possibilities. As for the modal verbs in German, there is a dedicated tag for modal verbs in the Colege corpus and it may be identified very easily by the CQL:26 [tag="VMFIN| VMINF"] 26 The VMFIN tag means a finite form of a modal verb, the symbol “|” OR and VMINF means an infinitive form of a modal verb. Table 5: Modal verbs in Legal German Figure 9: Modal verbs in Legal German Obrázok, na ktorom je vnútri, Ruské koleso Automaticky generovaný popis Figure 10: Modal verbs with negations in Legal German As can be seen from the visualization, the modal verbs sollen (should, shall), dürfen (may), können (can) can be associated directly with the negation nicht (not) (similar to keine none), but the verb müssen (must) does not take a negation. Therefore, when comparing the situation in Legal German vs. Legal Chinese, it is clear that the collocational preferences at the negation are different. 4 Conclusion In this article, we have briefly demonstrated the whole process of a language data visualization – from retrieving, via data editing to the visualization. We have shown some examples of the visualization. In the end, there is still one question to answer: is this kind of visualization useful? We think that this type of visualization is primarily intended for the area of language acquisition. We believe that visualization can help get a basic overview of the examined data – whether it is a view of the language register (as in our case), or to a literary work of one author, or else just to compare the collocability of individual words (tokens). With appropriately selected parameters and the number of nodes, it is possible to very clearly show typical features of a text, register, or the relation between words. 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Acta Linguistica Asiatica, 12(1), 37-58. https://doi.org/10.4312/ala.12.1.37-58 Python. (n.d.). Retrieved March 15, 2022, from https://www.python.org Pyvis. (n.d.). Retrieved March 16, 2022, from https://pyvis.readthedocs.io/en/latest/# Rýchly, P. (2008). A Lexicographer-Friendly Association Score. In P. Sojka & A. Horák (Eds.), Recent Advances in Slavonic Natural Language Processing (pp. 6-9). Masaryk University. VIS.JS. (n.d.). Retrieved March 16, 2022, from https://almende.github.io/vis/docs/network/ Choice Between the Synonymous Pairs of Sutoppu and Teishi: A Case Study on Synonyms of Western Loanwords and Sino-Japanese in Modern Japanese Based on Corpus DENG Qi School of Foreign Studies, Northeastern University, China dengqixq123@gmail.com Abstract This paper discusses the results of a corpus-based study on the usage and functions of the western loanword sutoppu and its synonymous Sino-Japanese, teishi. Our analyses focus on the following four perspectives: (1) frequency, (2) conjugation types, (3) characteristics of genres used, and (4) collocations. The results show that sutoppu is used mostly in a causative form, implying something compulsory or intentional, whereas teishi is mostly used in its passive form to imply inevitability. In addition, sutoppu emphasizes instantaneity and has the meaning of intentionally stopping something with great resistance. Whereas teishi permits a certain duration of time and describes the state of being stopped. Keywords: western loanwords, Sino-Japanese words, sutoppu, teishi, synonyms Povzetek Clanek obravnava rezultate korpusne študije o uporabi in vlogah novejše prevzete besede sutoppu in njene sino-japonske sopomenke teishi. Analize se osredotoca na naslednje štiri vidike: (1) pogostnost, (2) vrste spreganja, (3) znacilnosti uporabljenih uporabljeni žanrov in (4) kolokacije. Rezultati kažejo, da se sutoppu vecinoma uporablja v vzrocni obliki, kar nakazuje na obvezno ali namerno dejanje, medtem ko se teishi vecinoma uporablja v pasivni obliki in s tem izraža neizogibnost. Poleg tega teishi dovoljuje dolocen cas izvedbe oziroma opisuje stanje ustavljanja, sutoppu pa poudarja trenutnost in ima pomen namernega ustavljanja necesa z velikim odporom. Kljucne besede: novejše prevzete besede, sino-japonske besede, sutoppu, teishi, sinonimi 1 Introduction Japanese vocabulary can be classified into four lexicon strata according to its origin: native (or Yamato), western loanwords, Sino-Japanese words, and hybrid vocabulary (Sugimoto & Iwabuchi, 1994; Ito & Mester, 1999; Nihongogakkai, 2018). Among the aforementioned four strata of Japanese, western loanwords and Sino-Japanese can function as verbs by adding suru to the noun. It should be noted that there are many synonymous pairs between suru-verbs in western loanwords and Sino-Japanese words, and their proper usage is one of the major difficulties for learners of Japanese. The reason why learners feel it difficult to learn the distinctive usage of the synonymous suru-verb in western loanwords and Sino-Japanese can be summarized as follows: (1) western loanwords are one of the most difficult strata to learn, and the acquisition of western loanwords is accompanied by various difficulties (Jinnai, 2008, Yamasita et al., 2018). (2) Moreover, it has been pointed out that there is no description in dictionaries on how to use them correctly (Yamashita et al., 2018). Although there have been some case studies on the criteria for the use of synonymous suru-verb pairs in western loanwords and Sino-Japanese, it is clear that there is still a lack of basic information to help learners distinguish the difference in the usage (Mogi, 2015). To address the above-mentioned problems, in this study, we investigate the semantic differences between suru-verb western loanwords and Sino-Japanese, by taking the pair of stoppu and teishi as an example. Regarding the selection of the target words in this study, Yamashita et al. (2018) took up 9 pairs of synonymous suru-verb in western loanwords and Sino-Japanese and conducted an awareness survey among 110 native Japanese speakers. Yamashita’s study revealed that 7 of the 9 pairs can be classified into three major types, while the difference between 2 pairs (....stoppu and ..teishi, ...tesuto and ..shiken) cannot be well explained. However, Yamashita (2018) focused his investigation on the introspection of native speakers. Since a corpus-based study is considered valid when the introspection of native speakers does not work (Ishikawa, 2012), this study will attempt to elucidate the usage of ....sutoppu (hereinafter referred to as sutoppu) and ..teishi (hereinafter referred to as teishi) as an example, to cover the first limitation. 2 Literature review The study of synonyms has been a fruitful area of corpus linguistics (Gries & Otani, 2010), which is discussed in many introductory books on corpus linguistics, such as Kennedy (1998), McEnery & Wilson (2001), etc. Corpus data can not only provide insights into naturally occurring language (Sinclair, 1991) but are also regarded as an effective tool to distinguish the differences between synonyms (Biber et al., 1998; Hunston, 2002; Moon, 2010). Besides the works which have investigated the differences between synonyms using corpora in English (Biber et.al, 1996; Liu, 2010; Chuang, 2011; etc.), many studies have compared the semantic functions of synonyms in Japanese (Sugimoto, 2009; Shinya, 2010; Zhao, 2013; etc.). Regarding the works that have compared the semantic functions of synonymous western loanwords and Sino-Japanese, for example, Miyata & Tanaka (2006) took up the western loanword ...risuku and compared it with its synonyms ..kiken, ...kikensei (all of which mean “a risk”) by using a newspaper database (Asahi, Mainichi, and Yomiuri newspaper from 2003 and 2004). Miyata (2007) compared ....meritto and its synonym ..riten (both of which mean “a merit”) also by using a newspaper database (Asahi, Mainichi, and Yomiuri newspapers from 2003, 2004, and 2005). Sato (2013) compared ...mudo with ...fun’iki (both of which mean “atmosphere/mood”) using a newspaper database (Asahi newspaper) and clarified the semantic features of each. However, there are not so many studies that have compared synonymous suru-verb western loanwords and Sino-Japanese. The following is an overview of studies on synonymous pairs between suru-verb western loanwords and Sino-Japanese from the following two perspectives: the qualitative survey on the awareness of native Japanese speakers, and quantitative surveys of the corpus. Regarding the awareness survey, Yamashita et al. (2018) conducted a survey among 110 native Japanese speakers (teachers and students) to clarify the differences between synonymous suru-verbs as either western loanwords or Sino-Japanese. The task was two-fold: the first was sentence production, in which the participants were asked to write down sentences they could think of, using each of the synonyms, and the second was freewriting about their findings on the differences in the usages of the same synonyms. Results revealed that 7 of the 9 pairs are classified into three major types: (1) differences are seen in terms of the semantic nuance (e.g. ....kaishi-suru/ ......sutato-suru [begin]), B(2) differences are seen in terms of the number of senses (e.g. ....tenken-suru/ ......chekku-suru [investigate, check]), and (3) differences are seen in terms of the range of use (e.g. ....renshu-suru/ ........toreningu-suru [train, have a physical practice]). However, the difference between the two pairs (....stoppu and ..teishi, ...tesuto and ..shiken) could not be well explained. About the quantitative surveys, Chen (2014) used a newspaper database to clarify the semantic frames of western loanwords, ..kea, and Sino-Japanese, ..kaigo (both of which mean “care”) by classifying the co-occurrences of these two words. Mogi (2015) conducted a survey using the Balanced Corpus of Contemporary Written Japanese to compare the similarities and differences between .....maku-suru and ....kiroku-suru (all of which mean “to mark”) from the perspective of feature genres and co-occurring objects. Although these studies have contributed a lot to a better description of the differences between synonymous western loanwords and Sino-Japanese, there is still room for improvement both in the database used as well as in the perspectives investigated. Regarding the database, many studies use relatively small databases, especially newspaper databases (Miyata et al., 2006; Miyata, 2007; Sato, 2013; Chen, 2014). As for the perspectives, there are many studies that focus on the frequency of appearances and collocations (Miyata et al., 2006; Miyata, 2007; Chen, 2014; Mogi, 2015), while only a few studies focus on the parts-of-speech (conjugation types) and characteristically used genres. Frequency and collocations may be considered a useful measure in identifying the differences between synonyms (Biber et.al, 1998; Evison, 2010; Aroonmanakun, 2015), and the preferable register and/or part-of-speech in which the words appear may also help students to understand the differences (Shaw, 2011; Phoocharoensil, 2020). Therefore, this study takes up stoppu and teishi as an example to clarify the differences in semantic properties from the following four perspectives: (1) frequency of appearance, (2) parts of speech and conjugation types, (3) characteristically used genres, and (4) collocations. 3 Aims and methodology This section outlines the research questions, data, and methodology used in this study. We give an overview of the definitions of the two words in several dictionaries in Section 3.1 and set out research questions in Section 3.2. The compilation of the corpora is delineated in Section 3.3. The methodology employed to address the research questions is described in Section 3.4. 3.1 Dictionary descriptions of sutoppu and teishi Prior to conducting the survey, we first refer to the dictionary definitions of sutoppu and teishi in four kinds of Japanese-Japanese (JJ) and Japanese-English (JE) dictionaries. The definitions in JJ are translated into English by the author. Definitions related to technical terms are excluded. In these definitions, both sutoppu and teishi mean to stop and to desist, and there is no specific information on the conjugation types or genres in which words are likely to be used. Therefore it is considered to be highly difficult for learners to understand the specifics of usages of the two words by looking up a dictionary. To better distinguish these two words according to their actual usages, further investigation on how these two words are used is needed. Table 1: Definition of sutoppu and teishi in dictionaries Source stoppu teishi JJ: ... Daijirin (.)...(1)............(2)....... (mei)suru. (1) Tomaru koto. Yameru koto. (2) [tomare] no shingo. (1) to stop. (2) stop signal. (.)...(1).......................(2)........................ (mei) suru. (1) Ugoiteita mono ga tomaru koto. Mata, tomeru koto. (2) Shiteita koto wo yameru koto. Mata, yame saseru koto. (1) To stop something that was moving. (2) To stop doing what you were doing, or to make someone stop. JJ: ... Shin-Meikai (1)[-..]......(2)...(....) (1) [-suru] tomaru koto. (2) tomare (no shirushi). (1) to stop. (2) a signal sign to stop.) [-..](1)[.........].........(2).....(..).... [-suru] (1) [Idou shiteiru mono ga] chuuto de tomaru koto. (2) Katsudou wo yame (sase) ru koto. (1) To stop a moving object. (2) To stop an activity. JE: Geneus n. stop. v.stop, halt. n. (1) a stop; (2) suspension. v. (1) stop; (2) come to a stop (halt); (3) suspend. JE: Wisdom n. a stop. v. stop. n. (1) (a) stoppage, a stop; (2) (a) suspension. v. (1) stop, pause; (2) cease; (3) suspend. 3.2 Aims and a research question This study will elucidate the use of suru-noun western loanwords and Sino-Japanese, taking sutoppu and teishi as an example, for which the differences in the meaning are sometimes unknown even to Japanese native speakers. Although there are many linguistic perspectives regarding their semantic functions, this study elucidates the distinction between sutoppu and teishi from four perspectives: (1) frequency, (2) conjugation types, (3) characteristically used genres, (4) collocations. Specifically, we set up the following 4 research questions (RQs). 1. What are the differences in the frequency of use? 2. What are the differences in conjugation types? 3. What are the differences in the genres used? 4. What are the differences in collocations? To verify these research questions based on corpus data, we further developed hypotheses for each question to make the verification process more systematic. 1. (H1) According to some previous studies, the frequency of western loanwords is higher than that of Sino-Japanese (e.g., Miyata (2007) (....meritto vs. ..riten: 7898 vs. 5125)), while others found the frequency of Sino-Japanese to be higher than western loanwords (e.g., Miyata (2006) (...risuku vs... kiken: 4671 vs. 8091), Chen (2014) (..kea vs. ..kaigo: 1097 vs. 3766)). Since sutoppu and teishi are expected to be used more frequently in socio-economic contexts, such as .....sutoppu daka for stock prices and ....kinkyu teishi in issues regarding nuclear power plants, they are closer to ...risuku/ ..kiken and ..kea/ ..kaigo described in the studies above, and because of this, we expect the frequency of Sino-Japanese to be higher. 2. (H2) Regarding the conjugation types, in lexical descriptions, there was no clear difference in verbosity and intransitivity, although details of the glosses were slightly different. On this basis, it is expected that the part-of-speech and conjugation types of the two words will be equivalent. 3. (H3) Regarding the characteristic genres in which they are used, it was pointed out that western loanwords are more likely to be used in a more casual style and in everyday conversation, while Sino-Japanese words are relatively more likely to be used in a more formal style (e.g. Zhou (2014), Baba (2018)). Consequently, it is expected that sutoppu will be used more frequently in less formal genres like ‘blogs’ and ‘magazines’, while teishi will be used more frequently in more formal genres like ‘white papers’ and ‘laws’. 4. (H4) Regarding the collocations, (1) since western loanwords are assumed to be less restrictive in terms of word types that they co-occur with (e.g. Chen (2018) stated that ..kea co-occurs with native Japanese, Sino-Japanese and western loanwords, but ..kaigo mainly co-occurs with native Japanese and Sino-Japanese), it is expected that sutoppu co-occurs with native Japanese, Sino-Japanese and western loanwords, but teishi mainly co-occurs with native Japanese and Sino-Japanese. (2) In addition, as mentioned in Miyata et al. (2006), when there is an existing word with a similar meaning, the reason for the existence of the western loanwords is that there is a certain separation between it and the existing word. So we expect that there will also be a difference in the co-occurrence of sutoppu and teishi. 3.3 Corpora In this study, we use the Balanced Corpus of Contemporary Written Japanese (...............Gendai nihongo kakikotoba kinko kopasu, henceforth BCCWJ), which is the first large-scale balanced corpus on the Japanese language developed mainly by the National Institute for Japanese Language and Linguistics (NINJAL). To capture the diverse reality of the written language, BCCWJ consists of three subcorpora (publication subcorpus, library subcorpus, and special-purpose subcorpus) and covers a wide range of text registers including ‘books in general’, ‘magazines’, ‘newspapers’, ‘governmental white papers’, ‘best-selling books’, ‘internet bulletin-board’, ‘blogs’, ‘school textbooks’, ‘minutes of the national diet’, ‘publicity newsletters of local governments’, ‘laws’, and ‘poetry verses’. The amount of data is 100 million words, which is comparable to BNC (Ishikawa, 2012, Maekawa et al., 2014). 3.4 Methodology Regarding the RQ1 (frequency of use), we investigate the frequency of sutoppu and teishi in the BCCWJ. For RQ2 (conjugation types), we first investigate the frequency with which the two words sutoppu and teishi are used as nouns and verbs respectively. We follow the conjugation patterns of verbs in BCCWJ (11 categories including negative form, continuous form, hypothetical form, imperative form, and others). The specific conjugation types are shown in Table 2. English translations are taken from A Handbook of Japanese Grammar Patterns for Teachers and Learners (Jammassy, 2015). Table 2: The conjugation types of verbs Conjugation patterns Form Example ...renyou-kei conjunctive form .shi- polite form ...shi-masu te-form ..shi-te/ .... shi-mashite ta-form ..shi-ta/ ....shi-mashita ...rentai-kei dictionary form ..suru ...shuushi-kei dictionary form ..suru ...katei-kei conditionals (ba-form) ...sure-ba .....ishisuiryo-kei volitional form ...shi-yo ...kano-tai potential form ...dekiru/ ....dekimasu ...meirei-kei command form ..shiro/ .. seyo ...mizen-kei (...sareru) passive form ...sareru/ .... saremasu ...mizen-kei (...saseru) causative form ...saseru/ ....sase-masu ...mizen-kei (.se) se-form .se- ...mizen-kei (..ippan) negative form ...shi-nai Regarding the RQ3 (genres), we investigate the frequency of sutoppu and teishi in 12 genres of BCCWJ (excluding prosody). In order to make appropriate comparisons between the genres, we adjust the raw frequency into frequency per million words. Regarding the RQ4 (collocations), we conduct correspondence analysis to compare the co-occurences of the two words. Correspondence analysis (Benzécri, 1973; Greenacre, 1984, 2017; etc.) has recently been adopted in many corpus studies. It is a method of data visualization by translating two-way and multi-way tables into more readable graphical forms (Greenacre, 2017; Beh & Lombardo, 2021). Correspondence analysis simultaneously classifies cases and variables, which are both called categories, and displays the internal structure existing in a set of item-category data in a simple two-dimensional scatter plot, which enables us to intuitively examine how the categories or items are mutually interrelated and grouped (Ishikawa, 2016). Specifically, we separate both sutoppu and teishi into two groups: when either used as nouns or as verbs. (1) When the two words are used as nouns, we extract the first word and the second word on the left of sutoppu or teishi, and the first word on the right of sutoppu or teishi. In addition, we sort the collocations and extract the top 15 words (if there was a word whose frequency matched that of the 15th word, all words with the same frequency were included). Furthermore, we make a frequency table with each genre of sutoppu and teishi as the first item (18 genres excluding the genre in which the frequency of the top word is less than 20), and the top words of co-occurrence as the second item (84 words excluding redundancy), and then conduct a correspondence analysis. (2) When the two words are used as verbs, we first manually extract the objects, and then extract the top 30 words (if there is a word whose frequency agrees with the 30th word, we include all words whose frequency are the same). Next, we make a frequency table in which each genre of sutoppu and teishi is the first item (10 genres excluding the genre in which the frequency of the top word is less than 20), and the top words of the objects are the second item (64 words excluding duplicates) and conduct a correspondence analysis. 4 Results and discussion This section presents the results and discussions on each of the four perspectives described above: frequency (RQ1) in Section 4.1, conjugation types (RQ2) in Section 4.2, characteristically used genres (RQ3) in Section 4.3 and collocations (RQ4) in Section 4.4. 4.1 The comparison of frequency First, the frequency of sutoppu and teishi in BCCWJ are shown in Figure 1 below. 3694 1123 0 500 1000 1500 2000 2500 3000 3500 4000 teishi sutoppu teishi sutoppu Figure 1: Frequency of sutoppu and teishi Figure 1 shows that teishi is used more than three times as often as sutoppu, suggesting that Sino-Japanese is used with a much higher frequency. As mentioned in the hypothesis, frequency comparisons between Sino-Japanese and western loanwords with similar meanings have been conducted in many studies, but the results have been disparate. For example, Miyata (2006) found that the frequency of the Sino-Japanese, ..kiken, was 30% lower than that of the western loanwords, ...risuku. On the other hand, Chen (2014) showed that the frequency of the Sino-Japanese, .. kaigo, was 2.4 times higher than that of the western loanwords, .. kea. In this study, teishi is 2.3 times more frequent than sutoppu, showing a similar result to the use of ..kaigo and ..kea in terms of frequency relationship. Then, what causes the selection rate of Sino-Japanese for ..kiken/ ...risuku to be low and that for teishi/ sutoppu high? Firstly, as mentioned in the hypothesis, there is a difference in the contexts in which the words are used. In contexts closer to daily life, western loanwords are widely used to replace Sino-Japanese, while words that are frequently used in social and economic contexts, Sino-Japanese with high formality may be preferred. Secondly, the difference may be caused by the part-of-speech nature of western loanwords. ...Risuku is a pure noun that cannot be inflected, while sutoppu is a noun that can be inflected and used as a verb. In general, nouns refer to concrete objects, especially to specific, static objects with clear contours, so the one-to-one correspondence between an object and a word is strong and difficult to be replaced with other words. Verbs, on the other hand, are words that express the totality of changing motion, so their indicative content is usually broader than that of nouns. For example, if we compare the content implied by the noun ‘oranges’ with that implied by the verb ‘eat’, we find that the latter is much broader, more ambiguous, and less semantically specific. As a result, the strength of the one-to-one correspondence between verbs can be relatively lower, and as a result, a verb can be more easily substituted by another word. For this reason, the noun ...risuku is rarely substituted by ..kiken, while sutoppu, which can be used both as a verb and a noun, may frequently be substituted by teishi. This explanation also applies to the case of ..kaigo and ..kea, which also have a high rate of Sino-Japanese selection. Based on the above, the following two sections will look at conjugation types (parts of speech) (RQ2) and style (genre) (RQ3) separately. 4.2 The comparison of conjugation types Next, we investigate the frequency of noun and verb uses of sutoppu and teishi, respectively. The results are shown as Figure 2 below. 1387(38%) 311(28%) 2306(62%) 812(72%) 0% 20% 40% 60% 80% 100% teishi sutoppu verb noun Figure 2: Frequency of the noun and verb uses of sutoppu and teishi Figure 2 shows that both words are used more as nouns than verbs, however, the proportion of noun use of sutoppu was 72%, which is 10% higher than that of teishi. Based on the BCCWJ's classification of verb conjugations, we can classify the verb uses of the two words as shown in Figures 3 and 4 below. renyo-kei50% rentai-kei13% shushi-kei9% katei-kei0% mizen-kei (sareru)5% mizen-kei (saseru)21% mizen-kei (se)1% mizen-kei (ippan)1% mizen-kei28% renyo-kei rentai-kei shushi-kei katei-kei mizen-kei (sareru) mizen-kei (saseru) mizen-kei (se) mizen-kei (ippan) Figure 3: Conjugation types of sutoppu used as a verb renyo-kei53% rentai-kei12% shushi-kei11% katei-kei1% isisuiryo-kei0% meirei-kei0% mizen-kei (sareru)10% mizen-kei (saseru)9% mizen-kei (se)1% mizen-kei (ippan)3% mizen-kei23% renyo-kei rentai-kei shushi-kei katei-kei isisuiryo-kei meirei-kei mizen-kei (sareru) mizen-kei (saseru) mizen-kei (se) mizen-kei (ippan) Figure 4: Conjugation types of teishi used as a verb Figures 3 and 4 show that the causative-passive form of sutoppu is 21.22%, which is 126.47% more than teishi, and the passive form of sutoppu is 4.82%, which is 51.56% less than teishi. In other words, sutoppu is used mostly in the active form and implies the meaning of compulsory and intentional, while teishi is used mostly in the passive form and may include the meanings of being situational passive, or inevitable. As stated in the hypothesis, the part-of-speech and conjugation types of the two words seem to be equivalent from the point of view of dictionaries, but the results suggest that, contrary to the hypothesis, sutoppu is used more often as a noun, and is more likely to include the meaning of compulsory. If this point could be added to the dictionary, it would make it easier to understand the usage of the two words. 4.3 The comparison of genres Concerning RQ1 and RQ2 above, we investigated the differences between sutoppu and teishi from two perspectives, frequency, and conjugation types. The results show that (1) in terms of frequency, teishi is used more than twice as often as sutoppu, (2) in terms of the conjugation types, sutoppu has more noun usages than teishi, and sutoppu has been used in its causative form one time more than teishi, emphasizing its meaning of forceful. So what differences exist in the genre preferences of the two words? The following are the results of a survey of the frequency of the two words in each genre of the BCCWJ. Table 3: Frequency and ratio of sutoppu and teishi used for each genre Genres (Abbreviations in BCCWJ) sutoppu teishi PMW ratio (%) PMW ratio (%) books published book(PB) 7.64 6 35.93 5 library book(LB) 7.37 6 24.46 4 best-selling books (OB) 5.61 4 20.58 3 magazines (PM) 25.87 20 29.92 4 newspapers (PN) 15.33 12 66.41 10 blog (OY) 30.61 24 24.92 4 school textbooks (OT) 2.15 2 25.85 4 publicity newsletters of local governments (OP) 13.32 10 37.55 5 minutes of the national diet (OM) 9.21 7 42.72 6 bulletin-board (OC) 9.36 7 38.22 5 white papers (OW) 3.48 3 56.52 8 laws (OL) 0.00 0 293.75 42 Three inferences can be made from Table 3. To begin with, sutoppu is used much more in the ‘blogs’ and ‘magazines’ genres, and also seen in the ‘newspapers’ and ‘ publicity newsletters of local governments’ genres, but not at all in the ‘laws’ genre. It seems that sutoppu was found to be favored in more casual contexts. Furthermore, teishi is used more in the ‘laws’ genre and to some extent also in the ‘newspapers’ genre. In other words, the use of teishi is preferred in more official contexts. The hypothesis stated that teishi is more frequently used in more formal genres than sutoppu because western loanwords are more likely to be used in a more casual style and daily conversation, while Sino-Japanese are more likely to be used in a more stiff style and official contexts. On these two points, we can say that the hypothesis is supported. Finally, As for bias toward specific genres, teishi is overwhelmingly used in the ‘laws’ genre, which is more biased than sutoppu. It has often been pointed out that western loanwords have the function of creating a sense of freshness and making positive use of stylistic differences, but the present results suggest that Sino-Japanese may also have the function of highlighting differences between highly formal styles and other genres. 4.4 The comparison of collocations Last but not least, we will focus on the words that co-occur with the two words for comparison. We will first look at the case of noun usage. Figure 5: Scatter plots of feature words co-occurring with two words used as a noun Figure 5 shows the results of the correspondence analysis which has the genres of sutoppu and teishi as first items and the 84 top co-occurring words as second items. The contribution of dimension 1 (vertical axis) and dimension 2 (horizontal axis) are 17.25% and 12.59%, respectively, which explains 29.83% of the total. As seen in Figure 5, sutoppu and teishi are separated on the left and right sides of the figure, and the words characteristic of the two words can be summarised in Table 4 below. Table 4: Characteristic words for sutoppu and teishi sutoppu teishi left1 ..wan (one), ......aidoringu (idling), ..suchi (numerical value), .en (yen), .hon (quantity unit), ..basu (bus), ...bitto (bit), .kai (quantity unit), ....dokuta (doctor), ...etchi (etch), .....sutoraido (stride) ..shikko (execution), ..riyo (use), ..sogyo (operation), ..kokyu (breathing), ..kino (function), ..shikyu (payment), .kokoro (heart), ..shinhai (cardiopulmonary), ..eigyo (business), ..gyomu (work), ..menkyo (license), ..shutsujo (one's turn to go on satge), ..torihiki (transactions), ..shiko (thinking),..ichiji (for a time), .teki (suffix), ....enjin (engine) right1 ..gyosei (administration), ....sabisu (service), ..chikyu (earth), ..ondan (global warming), ...bando (band), ..sakusen(strategy), ..rosu (loss), .taka (a limit high of a stock price), .yasu (a limit low of a stock price), ...rampu (lamp), .....moshon (freeze-fram), .so (layer), .go (word), ...botan (button) ..nado (etc.), ..joken (condition), .kao (face), ..tekiyo (application), ..shobun (punishment), ..sochi (measure), ..kikan (period), ..meirei (command), ..jotai (state), ..ichi (location), .chu (in), .sen (line), .go (after), ..sochi (device), .ji (time) right2 ....sabisu (service), ......shoppingu (shopping), ..ondan (warm), .za (the), .ka (-ificaion), ..hirei (proportion), ...goru (goal), ...kakeru (make), ..meigara (brand name), ...kakaru (make), ..aru (be) ..meirei (command), ...meizuru (command), ..nado (etc.), ..mono (person), ..yoru (according to), ...motomeru (demand), .e (to), .. jogai (exclusion), ..okonau (do), ...botan (button), .. jotai (state), ..naru (become), ..iu (say), ..suru (do) Regarding the word types of characteristic words, as hypothesized, sutoppu co-occurs with native Japanese (e.g. . taka, . yasu), Sino-Japanese (e.g. .. suchi, ..hirei) and western loanwords (e.g. .... dokuta, ..... moshon), but teishi mainly co-occurs with Sino-Japanese (e.g. .. riyo, .. shikyu ). Furthermore, in the words co-occurring with sutoppu, many words that express the characteristics of the point at which the stop occurs, such as .. suchi (numerical value), . taka (maximum allowable single-day gain (stock exchange)), or . yasu (maximum allowable single-day loss (stock exchange)), whereas, in the words co-occurring with teishi, there are many words with continuity, such as .. kikan (period), .. jotai (state), and . chu (middle). In other words, sutoppu often refers to a point of stopping and rarely includes the meaning of continuation of time, whereas teishi is allowed to mean the continuation of time. Also, sutoppu is often used to emphasize the action of stopping something that is moving, or the act of trying to stop, such as ........ dokuta sutoppu (doctor stop: a doctor forbids a patient to do something they think will prevent a disease or a disability from worsening or leading to death) or ......... sutoppu chikyu ondanka (stop global warming) while teishi is often used to emphasize the state or the result of being stopped, such as .... menkyo teishi (license stop) or .... eigyo teishi (business stop), and to express the state of stopping bodily functions, such as .... kokyu teishi (stop breathing) or .... shinhai teishi (cardiopulmonary stop). The specific examples are given as follows. (1) ...............,......................,... Kono mondai ni sutoppu wo kakeru tame, muda na enerugi wo shiyo shinai setsuyakugata no kurashi ya, shizen enerugi e no tenkan nado ga motomerareteimasu. .In order to stop this problem, we need to save energy and switch to renewable energy sources.' (2) ..........,....................,........ Ku wa mokuhyo no tassei ni muke, shomeisetsubi ya kuchosetsubi wo kokoritsu na mono ni koshinshi, sochaku kano na subete no choyusha ni aidoringu sutoppu sochi wo sochaku nado, sossenshite onshitsukoka gasu no haishutsu yokusei ni mo torikundeimasu. .In order to achieve the target, the ward is taking the initiative to reduce greenhouse gas emissions by upgrading their lighting and air conditioning systems efficiency, and installing idling stop devices in all government-owned vehicles where they can be installed.' (3) ..,...................................., Ato, fudosan eigyo no rodo jittai wa jikan ni naosu to rodo kijunho ijo ni hataraiteiru kesu ga oku, sono mama tetsuzuki to kaisha ga eigo teishi ni natte shimaimasu. .Also, in many cases, the actual labor of real estate salespeople is more than the labor standard law allows, if it is measured in hours. If the practise is not changed, the company will be suspended from business.' (4) ..,..................CPR(.....)........., Toku ni, shinhai teishi jotai no shobyosha no kyumeiritsu kojo ni shiCPR (shinhai soseiho) no shutoku ni shugan wo oki,katsu kunren-yo ningyo nado wo mochiita jumin taikengata no fukyu keihatsu katsudo no sekkyokuteki na suishin ga motomerareteiru. .In particular, there is a need to focus on the learning of CPR (cardiopulmonary resuscitation) to improve the lifesaving rate of injured people in cardiopulmonary arrest, and to actively promote hands-on educational activities using training dolls.' The findings above can be summarised as in Figure 6. Figure 6: Illustration of the difference in noun usage between sutoppu and teishi As shown in Figure 6, sutoppu emphasizes instantaneity and the action of stopping, whereas teishi allows for a certain amount of time and denotes the state of being stopped. Next, we will look at cases where sutoppu and teishi are used as verbs. Figure 6 shows the results of the correspondence analysis with each genre of sutoppu and teishi as the first items and the 84 top co-occurring objects as the second items. As already mentioned, sutoppu is not used at all in the ‘laws’ genre, so we exclude the ‘laws’ genre here. The contribution rates of dimensions 1 and 2 are 30.23% and 18.14%, which explain 50.24% of the total. As can be seen from Figure 7, each genre of sutoppu and teishi was found to be divided on left and right. Summarizing their respective characteristic words , we obtain the following Table 5. Figure 7: Scatter plots of feature words co-occurring with two words used as verbs Table 5 shows that in the feature objects of sutoppu, there are many words that semantically denote ‘something with high resistance or ongoing action’, such as ... gemu (game), .. butsuryu (logistics), and .. shien (support). On the other hand, in the feature object of teishi, there are many nouns related to machines, such as .. ressha (train) and ....enjin (engine), and nouns related to bodily functions, such as .. shinzo (heart) and .. kokyu (breathing), which express something with low resistance. Specific examples are given below. Table 5: Characteristic words for sutoppu and teishi Objects of Objects of teishi ..shiai (match), ...rain (line), .kane (money) ..shingi (deliberation), ..kensetsu (construction), ..butsuryu (logistics), ..hanno (reaction) ..koji (construction), ...kenkyuhi (research funds), ..sore (it), ..shien (support), ..yushi (loan), ....kotsukikan (transportation), ...hikoki (airplane), ..kodo (behavior), ..nagare (flow), .ku (phrase), ..rensho (consecutive victories), ..seisan (production), ...shiharai (payment), ..jikan (time), ..hakko (publishing) ......erebeta (elevator), ..yunyu (import), ..kyokyu (supply), ..shiko (thought), ..kairo (circuit (electric)), ..shori (processing), ..kokyu (breath),...pompu (pump), ..ugoki (movement),..ressha (train), ...genshiro (nuclear reactor), ..seicho (growth), .kuruma (vehicle), ..yushutsu (export), ..kino (function), ....enjin (engine), ..katsudo (activity), ...jidosha (automobile), ..saisei (regeneration), ..unten (operation), ..sagyo (operation), ..shinzo (heart),..shinkyu (payment), ....sabisu (services), ..jigyo (business), ..shiyo (use), ..riyo (use) (5) ...................,.......,...........,. harusaki na noni sujunen buri no daikampa ga otozure, yuki ga furi hajime, yagate mofubuki ni kawatte, oku no kotsu kikan ga sutoppu shi, mochiron hikoki mo tobazu... .Even though it was the beginning of spring, the first major cold wave in decades hit, and snow began to fall, which soon became a blizzard, stopping many transportation systems, and of course, flights.' (6) ..,...........,....................(PB35_00199) genzai, yoroppa no oku no kuni ga, imin no nagare wo sutoppu shiyo to shiteimasu. .Currently, many European countries are trying to stop the flow of immigrants.' (7) ...................,...........,...,..... kore wo tanabe kaijo hoambu tsushin sho ga jushin shita ga, kando ga hijo ni bijaku de ari, sara ni, shinsui de hatsudenki ga teishi shi batteri shiyo ni yoru soshin deatta tame yaku sampun de tsushin ga todaete shimatta koto nado kara, L go no sonan ichi wa nojimazaki no nampo to shika kakunin deki nakatta. .The Tanabe Coast Guard Station received the message, but the sensitivity was very weak, and the transmission was cut off after about three minutes because the generator was stopped by the flooding and a battery was being used for transmission.' (8) ........................,.............,. kega ya kyubyo nado de kokyu ya shinzo ga teishi shite shimatta baai, jinko kokyu ya shinzo massaji wa, chishiki ga nai to dekimasen. .If a person's breathing or heart stops due to injury or sudden illness, artificial respiration and cardiac massage cannot be performed without knowledge.' The above examples show that sutoppu can mean to deliberately stop something that is of high resistance or a movement in progress, and similarly, in its noun usage, sutoppu emphasizes the action of stopping. In example (5), interruption of traffic should be avoided (which leads to psychological resistance to the interruption of traffic), but the snow unavoidably stopped the traffic, anyways. In example (6), it is considered that there is great resistance from the immigrants who try to come in with a strong will. On the other hand, teishi often refers to stopping something with low resistance. In example (7), the subject of the action is a generator, and a generator does not have any intention of not wanting to stop, so teishi is chosen here. In example (8), the heart has already stopped spontaneously due to an injury or illness, and there is no particular resistance, so teishi has also been chosen here. Thus, sutoppu emphasizes sudden and forcible stopping which overcomes some kind of resistance, whereas teishi often describes things that have spontaneously stopped. 5 Conclusion In summary, this paper has attempted to elucidate the use of the semantic functions of the western loanword sutoppu and its synonymous Sino-Japanese word teishi from four perspectives: (1) frequency, (2) conjugation types, (3) characteristically used genres, and (4) collocations. The findings of this paper can be summarized as follows. Firstly, in terms of frequency, teishi is used more than twice as often as sutoppu, which may be caused by the contexts in which the words are likely to be used and the part-of-speech nature (see 4.1). Secondly, in terms of conjugation types (parts of speech), both words are used as nouns more frequently than as verbs, and sutoppu is used as a noun 10% more than teishi. In addition, sutoppu is used mostly in the causative form, implying something compulsory or intentional. Whereas teishi is mostly used in its passive form to imply inevitability (see 4.2). Thirdly, from the perspective of genres, sutoppu is less genre-biased and is preferred in more informal contexts. On the other hand, teishi has a greater genre bias and is preferred in more public contexts (see 4.3). Finally, in the case of collocations, when the two words are used as nouns, sutoppu emphasizes instantaneity and describes the action of stopping, whereas teishi permits a certain duration of time and describes the state of being stopped. When the two words are used as verbs, the characteristic objects of sutoppu semantically express something with high resistance or ongoing action, while the characteristic objects of teishi have many words which express something with low resistance. In addition, sutoppu has the meaning of intentionally stopping something with great resistance or stopping an action in progress, emphasizing the action of stopping, whereas teishi often refers to the state of being stopped (see 4.4). Since the first corpus-based dictionary Collins Cobuild Dictionary of English, compiled by John Sinclair and published in 1987, the way dictionaries were compiled which had relied heavily on the introspective judgment of native speakers had changed. At present, almost all English dictionaries for learners are corpus-based, but Japanese dictionaries for learners are few in number, and there are still no fully corpus-based dictionaries (Ishikawa, 2014). Many previous studies have pointed out that there is room for the contribution of corpora and corpus analysis methods in the development of Japanese dictionaries for learners (Sunakawa, 2011; Tanomura, 2010; Ishikawa, 2014). In this study, we expect to shed new light on the development of Japanese dictionaries for learners. Table 6 is an example of a dictionary description that utilizes the findings of the present study. As shown in Table 6, the use of the two words can be made clearer by adding the information of genre and conjugation types, as well as specific usage preferences. To conclude, this paper has elucidated the usage of sutoppu and teishi in terms of their semantic functions. However, there are some limitations. Firstly, only one pair of a western loanword and its synonymous Sino-Japanese word was observed. Secondly, the study does not incorporate native speaker reflections. We hope to address these points in our ongoing research. Table 6: Proposal for a new dictionary description sutoppu . Characterisitic genres: teishi . Characterisitic genres: .‘laws’ . ‘newspapers’ . When used as a noun: Meaning: Emphasizes the the state of . Examples of collocations: (1) ....riyo teishi (utilization stop) (2) ....shutsujo teishi (exit stop) (3) ....shinhai teishi (cardiopulmonary stop) (4) ....teishi jotai (stop status) . When used as a verb: meaning: Emphasizes stopping with . Examples of collocations: (1) .....katsudo wo teishi (stop activity) (2) .....kino wo teishi (stop function) (3) .......enjin wo teishi (stop engine) (4) .....kokyu wo teishi (stop breathing) References Aroonmanakun, V. (2015). Quick or fast: A corpus based study of English synonyms. LEARN Journal: Language Education and Acquisition Research Network, 8(1), 53-62. Baba, T. (2018). The possibility of studies of stylistic features of words using "writing style annotation for the library subcorpus of the BCCWJ" (in Japanese). Proceedings of Language Resources Workshop, 3, 241-256. Beh, E. J., & Lombardo, R. (2021). An introduction to correspondence analysis. John Wiley & Sons. Benzécri, J. P. (1973), L'Analyse des Données, Vol. I, La Taxinomie; Vol. II, L'Analyse des Correspondances. Dunod. Biber, D., Conrad, S., & Reppen R. (1996). Corpus-based investigation of language use. Annual Review of Applied Linguistics, 16, 115-136. Biber, D., Conrad, S., & Reppen, R. (1998). Corpus linguistics: Investigating language structure and use. Cambridge University Press. Chen, X. (2014). The Difference of the Meanings of Synonyms in Katakana and Kanji: The Semantic Difference of "Care" and "Kaigo" (in Japanese). The Ritsumeikan literature review, 637, 1438-1450. Chung, S. F. (2011). A corpus-based analysis of “create” and “produce”. Chang Gung Journal of Humanities and Social Sciences, 4(2), 399-425. Evison, J. (2010). What are the basics of analysing a corpus. In A. O’Keeffe & M. McCarthy (Eds.), The Routledge Handbook of Corpus Linguistics. (pp. 122-135). Routledge. Greenacre, M.J. (1984). Theory and Application of Correspondence Analysis. Academic Press. Greenacre, M.J. (2017). Correspondence Analysis in Practice (3rd ed.). Chapman & Hall/CRC. Gries, S. T., & Otani, N. (2010). Behavioral profiles: A corpus-based perspective on synonymy and antonymy. ICAME journal, 34, 121-150. Hunston, S. (2002). Corpora in Applied Linguistics. Cambridge University Press. Inoue, N., & Akano, I. (Eds.) (2013). The Wisdom English-Japanese Dictionary (3rd ed.). Sanseido. Ishikawa, S. (2012). A Basic Guide to Corpus Linguistics (in Japanese). Kabushiki Kaisha Hitsuji Shobo. Ishikawa, S. (2014). Cooccurrence network analysis for sophistication of dictionary definitions of Japanese synonymous words: possibility of corpus-based Japanese dictionaries. (in Japanese). The Institute of Statistical Mathematics cooperative research report, 308, 1-21. Ishikawa, S. (2016). Japanese polite sentence-final markers: desu, desuyo, desune, and desuyone A corpus-based analysis with a focus on frequency, collocation, and functional grouping. In J. Szerszunowicz, B. Nowowiejski, P. Ishida & K. Yagi (Eds.), Linguo-cultural research on phraseology, 3, 537-554. Jammassy, G. (2015). A Handbook of Japanese Grammar Patterns for Teachers and Learners. Kurosio Press. Jinnouchi M. (2009). Nihongo gakusyusya no katakana isiki to katakanago kyoiku (in Japanese). Language and Culture, 11, 47-60. Kennedy, G. D. (1998). An introduction to corpus linguistics. Routledge. Liu, D. (2010). Is it a chief, main, major, primary, or principal concern?: A corpus-based behavioral profile study of the near-synonyms. International Journal of Corpus Linguistics, 15(1), 56-87. Maekawa, K., Yamazaki, M., Ogiso, T., Maruyama, T., Ogura, H., Kashino, W., Koiso, H., Yamaguchi, M., Tanaka, M., & Den, Y. (2014). Balanced corpus of contemporary written Japanese. Language resources and evaluation, 48(2), 345-371. Matumura, A., & Sanseidohenshujo (Eds.) (2006). Daijirinn (3rd ed.). Sanseido. McEnery, T., & Wilson, A. (2001). Corpus linguistics: An introduction (2nd ed.). Edinburgh University Press. McEnery, T., & Hardie, A. (2014). Gaisetsu Kopasu Gengogaku: Shuho, Riron, Jissen. [Corpus linguistics: Method, Theory, and Practice]. (S. Ishikawa, Trans.). Hitsuji Shobo. (Original work published 2012). Minamide, K., & Nakamura, M. (Eds.) (2011). Genius Japanese-English Dictionary (3rd ed.). Taishukan. Miyata, K. (2007). Gairaigo "meritto" to sono ruigigo no imi hikaku shimbun wo shiryo to shite (in Japanese). Kokyo Baitai no Gairaigo: Gairaigo Iikae Teian wo Aasaeru Chosa Kenkyu. Kokuritsu Kokugo Kenkyusho. Miyata, K., & Tanaka, B. (2006). Gairaigo risuku to sono ruigigo no imi hikaku: kison no ruigigo wo motsu gairaigo no sonzai riyu (in Japanese). Proceedings of the Annual Meeting of the Association for Natural Language Processing, 12, 600-603. Mogi, T. (2015). A Corpus-based Study on Loanword Verbs in Japanese : A Case Study of maaku-suru (0.05). The results show that Liushu-based instruction indirectly predicts the level of ILEs through the IL2S of L2MSS components. In other words, IL2S mediated 76.46% of the total effect between Liushu and ILEs. OL2S has the strongest impact on ILEs at ß=0.340, p<0.01, followed by L2LE (ß=0.156, p<0.01). However, the result did not show a significant effect of Liushu-based instruction on OL2S and L2LE at ß=0.167, p>0.05 and ß=1.077, p>0.05, respectively. That is, at least one of a and b is insignificant. Thus, the researcher used bootstrap to test the significance of a*b. 95% BootCI represents the 95% confidence interval calculated by Bootstrap sampling. The 95% confidence interval containing zero, indicates that the mediation effect is not significant. As seen in Table 9, neither IL2S nor L2LE shows any significance. It can be concluded that IL2S and L2LE have no significant mediating effect between Liushu-based instruction and ILEs. In short, although Liushu-based instruction has no direct influence on ILEs, it can indirectly influence ILEs through IL2S, which is the mediator. Thus, H09 was rejected. 5 Discussion and conclusion This study investigated the impact of a 10-week Liushu-based instruction on Standard Chinese learners’ motivation and ILEs in Laos. Both the control group and the experimental group have almost identical motivation and ILEs in the independent sample t-test results of the pre-tests. The post-test results, however, show a slight change in the average scores in the motivation of the control group, while it increases from 107.80 to 110.59 in the experimental group. Furthermore, it is more obvious that the paired-sample t-tests showed that the experimental group had significant differences in IL2S and L2LE between the pre-test and the post-test. IL2S, meaning something that somebody wants to become, represents a person’s desire and as such is a powerful motivation for a student to learn a second language. In this process, Liushu-based instruction integrates the cultures to enhance learners’ interest in learning Chinese characters (Li, 2018). This may encourage learners to have a stronger desire to become the so-called ideal learners of Standard Chinese. L2LE is one’s experience in the learning environment influenced by teachers, courses, and teaching strategies. This result is in line with the view of Chen and Fu (2014) who believe that the application of Liushu can deepen learners’ understanding and memory of Chinese characters, increase their interest in Chinese character teaching, and strengthen its effect. The mediation test showed that Liushu-based instruction is likely to be a significant predictor of IL2S of L2MSS components. Although the paired t-test showed the L2LE changed significantly and positively in the experiment group, Liushu-based instruction was not a major predictor of L2LE in the regression analysis. This is an important finding because it emphasizes the need to deepen our understanding of Liushu-based instruction in motivational processes. A second key finding was the predictive influence of IL2S, OL2S, and L2LE on ILEs. OL2S is a stronger predictor than IL2S and L2LE. In other words, OL2S, which indicated the motivation from others’ expectations, played a larger effect on ILEs among learners. This finding is different from the results of Li and Zhang (2020) and Wong (2018) who found that IL2S exerted more influence on ILEs than OL2S among Tibetan learners and learners of Standard Chinese in Hong Kong, respectively. As Kormos & Kiddle (2011) stated, OL2S may have more relevance in the context where language education places great pressure on learners’ performance. This means that in Laos, the pressure exerted by others (e.g., parents, peers) motivates learners to put more effort into learning Standard Chinese. Unfortunately, the Liushu-based method did not have a positive impact on learners’ OL2S. To rephrase this result, motivation derived from external pressures or other people’s expectations could not change easily with changes in teaching methods. As a result, Liushu-based instruction can indirectly influence ILEs only through IL2S, which is motivated by the learner’s own desire for a second language. This study enhances understanding of the link between the instruction with Liushu-based instruction, L2MSS components, and ILEs among Standard Chinese learners in Laos. This study demonstrates that Liushu-based instruction is considerably beneficial for creating positive effects on learners’ IL2S and L2LE, which are the two components of motivation. It furthermore shows that Liushu-based instruction is good support in teaching Chinese characters. Teachers may use the source and structure of the characters involved in Liushu to make their teaching style more interesting, which is also the reason for the improvement of students’IL2S and L2LE. In addition, IL2S was found to mediate 76.46 % of the total effect of the relationship between Liushu-based instruction and ILEs, which means that teachers should pay more attention to the cultural functions carried by Liushu to improve students’ IL2S and motivate them to spend more efforts on learning Standard Chinese. However, it is important to note that applying Liushu-based instruction may be challenging for teachers of Standard Chinese. Although Chinese characters’ composition has a strong basis, modern Chinese characters have undergone great changes in form, which may cause learners to get bored. This requires Standard Chinese teachers to have a deep knowledge of Chinese characters to identify the relationship between their form and meaning. According to Gao (2018), only Standard Chinese teachers with sufficient knowledge can ensure good teaching results. It is important for teachers to understand the nature and characteristics of Chinese characters, as well as the evolution of Chinese characters, and teachers of Standard Chinese should possess enough professional knowledge to explain these phenomena. As a second recommendation, teachers should adjust Liushu-based instruction to the characteristics of learners. As stated by Gao (2018), learners of Standard Chinese that have relatively weak receptivity could easily get exhausted by even some simple Chinese learning. Adding the knowledge of Liushu (e.g., the evolution of characters) would likely increase their learning burden to the limits. Furthermore, in the current study, the learning time of Chinese characters was much longer in the experimental group than in the control group. Learning Chinese characters is the most time-consuming part of learning Standard Chinese for beginners. It is possible, however, that the use of Liushu for Chinese character learning is limited for intermediate and advanced learners since vocabulary and grammar learning will take more time and effort with the continuous increase of learning content. The learners’ Standard Chinese levels should therefore be considered when assigning Liushu to learners. Finally, teachers should limit the use of Liushu by considering the characteristics of Chinese characters. Chinese characters that are very different in shape or meaning from their ancient Chinese equivalents should no longer be explained by Liushu. As Fei (1998) stated, modern Chinese characters have undergone significant changes in form due to the emergence of simplified Chinese characters. It is true that Liushu can help students understand cultural meanings hidden in the original forms, however, it does little to help them memorize the characters in their simplified form if their present meaning had already lost the connection with the original meaning. Therefore introducing Liushu might even increase their workload. Last but not least, for learning pictographs, ideographs, and ideological compounds, it is best to focus on teaching simple components to avoid blindly tracing the source and causing more harm than good to the learners. 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System, 72, 201–214. https://doi.org/10.1016/j.system.2017.12.003 Xu, L. ....(2009). Liushu lilun yu duiwai hanzi jiaoxue............ Wenxue Jiaoyu (Xia)....(.)(08),146-147. Ye, J..... (2013). Laowo xuesheng xuexi hanzi de nandian ji duice tanxi ................. Xin Xibu(Lilun Ban)...(...), 7, 88+90. Zhang, C...., Lu, L...., & Zhejing, B. ..·.... (2021). Laowo hanyu jiaoxue xianzhaung ji fazhan yanjiu .............. Shijie Jiaoyu Xinxi ......, 2, 63-69. Exceptions vs. Non-exceptions in Sound Changes: Morphological Condition and Frequency LIU Sha Fukuoka University, Japan liusha@fukuoka-u.ac.jp Abstract This paper takes an approach different from most previous studies by firstly comparing exceptions with non-exceptions in the diphthongization of [i] to [ei] in Mandarin (AD 1324–Present) to locate factors that explain exceptions. Then it focuses solely on non-exceptional morphemes in this process by comparing morphemes at the forefront of this process with those undergoing it later to examine factors to explain morphemes leading this sound change. Statistical analysis shows that morphemes with the highest frequency among all related morphemes tend to be exceptions to diphthongization of [i] to [ei], and morphemes with high frequency among those non-exceptional morphemes tend to undergo this process earlier. In addition, the factor of frequency change, a proposal of this paper, is statistically significantly correlated with morphemes that lead diphthongization. The morphological condition has been rejected as statistically significant both for explaining exceptions to sound change and leading morphemes in sound change. Keywords: diphthongization, leading morphemes, frequency, frequency change, exceptions Povzetek Clanek uporablja nekoliko drugacen pristop v primerjavi z vecino prejšnjih študij; najprej primerja izjeme z neizjemami pri diftongizaciji [i] v [ei] v mandarinšcini (1324 AD–danes) z namenom poiskati dejavnike za razlago izjem. Nato se osredotoci izkljucno na neobicajne morfeme v tem procesu s primerjavo morfemov, ki so vodilni v spremembi, in morfemov, ki so spremembam podvrženi relativno pozno. Na ta nacin preucimo dejavnike in okolja, ki spodbujajo diftongizacijo [i] v [ei] . Rezultati statisticnih analiz kažejo, da so morfemi z najvišjo pojavnostjo med vsemi sorodnimi morfemi ponavadi izjeme pri diftongizaciji [i] v [ei], morfemi z visoko pojavnostjo med temi neobicajnimi morfemi pa so ponavadi podvrženi temu procesu prej. Poleg tega je dejavnik sprememb pojavnosti, ki je predlog tega prispevka, statisticno znacilno povezan z morfemi, ki so vodilni pri diftongizaciji. Morfološki pogoj je bil zavrnjen kot statisticno pomemben tako za razlago izjem pri glasovni spremembi kot tudi za vodilne morfeme v obravnavani glasovni spremembi. Kljucne besede: diftongizacija, vodilni morfemi, pojavnost, sprememba pojavnosti, izjeme 1 Introduction Previous studies have proposed morphological conditions and frequency to account for exceptions to sound change, and morphemes that are at the forefront of sound change (see e.g., Grimm, 1822; Postal, 1968; King, 1969; Antilla, 1972; Melchert, 1975; Vincent, 1978; Guy, 1991a; Pintzuk, 1991; Santorini, 1992, 1993; Kroch, 1994; Donohue, 2005; Bermúdez-Otero, 2007). However, disagreements concerning the role of the two mentioned factors in sound change are not rare. Although Postal (1968) and King (1969), among others, claim that the morphological condition has a role in sound change, Renwick et al. (2014) state that their results show little support for such a claim. Even scholars who claim that the morphological condition has a role in sound change cannot agree on its exact role: some claim that bound morphemes lead sound change, while others claim that it is free morphemes that lead it. Arguments concerning the frequency factor and sound change are more complex. A long-standing debate exists between authors claiming that the frequency factor takes a part in sound change and others claiming that sound change is independent of any frequency effects. The debate is further complicated by the fact that even authors who claim that frequency has a role in sound change cannot agree with each other on its exact role: some suggest that high-frequency morphemes lead sound change, while others argue that low-frequency morphemes are at the forefront of sound change, and yet there are those who claim that either high-frequency morphemes or low-frequency morphemes are the ones that lead sound change. In addition to the debate presented above, the present study notices another problem: scholars use different types of data to probe into the role of morphological condition and frequency in sound change. Some scholars compare exceptions and non-exceptions in a sound change process, while others compare morphemes that undergo a sound change process earlier with morphemes that undergo the same sound change later. This may be the reason that different scholars arrive at different conclusions: they had focused on different phases of sound change. This prompted the present study to inspect a sound change process from two aspects: (1) exceptions and non-exceptions in this sound change, and (2) morphemes that lead this sound change and morphemes that undergo it later. The paper firstly compares exceptions with non-exceptions in this sound change process to locate factors to explain exceptions in sound change. Then the paper compares morphemes that were at the forefront of this sound change with morphemes that underwent it later to locate factors to account for morphemes leading this sound change. This paper takes the diphthongization of [i] to [ei] in Mandarin (AD 1324–Present) as its data source. What makes data from Chinese interesting is that Chinese is a language with a long history and thus can provide various kinds of data for sound change discussion. In addition, not much attention has been paid to Chinese in sound change study (see e.g., Wang, 1969; Chen and Wang, 1975). Previous studies mainly take languages in the Indo-European language family as their focus. Since the sound change mechanism is supposed to be universal, it appears reasonable and necessary to examine data from languages belonging to various language families. In this respect, Mandarin is a good candidate since it belongs to the Sino-Tibetan language family and has not been widely discussed. Diphthongization of [i] to [ei] is a sound change process with exceptions that can provide data serving the proposal of the present study. Further, diphthongization of long high vowels is common in the world’s languages and thus possible to be compared with parallel processes in other languages. This paper is structured as follows. Section 2 discusses factors in the sound change in previous studies and presents a new proposal. Section 3 briefly sketches diphthongization of [i] to [ei] in Mandarin (AD 1324–Present). Section 4 carries out statistical analysis to locate factors to explain exceptions to the diphthongization of [i] to [ei] in Mandarin. Section 5 carries out another statistical analysis to examine factors to explain the morphemes leading this process. Section 6 puts forward some conclusions and issues relating to future research. 2 Previous studies Previous studies explain exceptions to sound change in terms of various factors. Among them, morphological condition and frequency are the two most debated (see e.g., Chafe, 1968; King, 1969; Postal, 1968; Antilla, 1972; Campbell, 1974). In this section, the paper firstly reviews the two factors and disagreements concerning them, and then gives its own proposal. 2.1 Morphological condition Postal (1968) and King (1969) can take the credit for noticing the possible role of morphological conditions in sound change although their claims have been questioned from many perspectives without resolution (Melchert, 1975). Following them, Zwicky (1970) discusses the auxiliary reduction in English. He (1970) notices that the rule which renders [i:y e:y u:w] to [i e u] and [a:y a:w] to [ay aw] applies only to pronominal forms ending in vowels (e.g., he, me, who) and followed by a contracted auxiliary other than [z]. A few years later, Rochet (1974) considers the change eN > aN in Old French and claims that this process was initiated as a morphological conditioned change. Malkiel (1976) discusses the diphthongizations in late Old Spanish, ié > i and ué > e, and argues that a set of morphological conditions can explain this phenomenon better than phonological conditions (see also Cerrón-Palomino, 1974; Johnson, 1982). 2.1.1 Exceptions vs. non-exceptions Postal (1968, p. 247) focuses on Mohawk, the language spoken by Mohawk people, and notices that [e] is regularly inserted into [kw] sequences except when the [k] is “the first person morpheme and the [w] the first element of the plural morpheme.” In his view (1968, p. 240), this language example shows that “nonphonetic morphophonemic and/or superficial grammatical structure” could also condition sound change (reviewed in Fudge, 1972; see also King, 1969). King (1969) is concerned with the final schwa deletion in Yiddish. According to him (1969), this rule does not apply when the final schwa is in an adjective inflectional ending. King (1969) concludes that this is evidence of morphologically conditioned sound change (reviewed in Robinson and van Coetsem, 1973; see also Antilla, 1972). Vincent (1978, p. 420) refers to the word-final schwa deletion in Spanish, and points out that the word-final schwa following a VC sequence is dropped, except in “the first person singular preterite of a number of irregular verbs …, the third person singular present indicative of all second and third conjugation verbs …, and the first and third singular present subjunctive of all first conjugation verbs.” Morphological conditions in King (1969) and Vincent (1978) are concerned with word class in a rough term: King (1969) is concerned with adjectives and Vincent (1978) is concerned with verbs. More recently, Crowley (1997, p. 243) focuses on Southern Paamese and Northern Paamese, two languages of Central Vanuatu, and reports “a correspondence of Southern Paamese /l/ to Northern Paamese /i/, /l/, or zero” in all word classes except verbs. According to Crowley (1997, p. 244), this is “a clear example of a sound change that does not involve purely phonological conditioning factors, but also … grammatical conditioning.” More specifically, this example shows that at least some sound changes apply only in some word classes (Crowley, 1997). What complicates the picture is that some scholars claim that it is morphosyntactic structure, instead of word class, that can explain exceptions to sound change. Donohue (2005) uses the voicing of voiceless stops in Palu’e to show that morphological conditions can explain exceptions to this sound change: bound grammatical morphemes seem to have fewer exceptions than free lexemes. Donohue (2005, p. 441) goes on with sound changes in Modern Indonesian and Bali-Vitu (Austronesian, Oceanic) to further support his claim, and concludes that sound change “depends as much on morphosyntactic information as it does on … phonotactic constraints, (phonological) conditioning environments, or changes in related sounds ….” Bybee (2002) focuses on word-final /t, d/ deletion in American English and concludes that bound morphemes can affect the deletion process. Guy (1991b, p. 2) also focuses on word-final /t, d/ deletion in American English and gives a more detailed conclusion: “underived or monomorphemic words such as mist, pact, undergo deletion at a higher rate than inflected forms such as past tense verbs like missed, packed” (see also Labov et al., 1968; Fasold, 1972; Guy, 1991a). Baranowski and Turton (2020) report a result similar to Guy (1991b) for word-final /t, d/ deletion in British English. It is at this point important to point out that although all scholars referred to in this subsection claim that morphological condition has a role in explaining exceptions to sound change, they hold different views concerning its exact effect. To exemplify, although Crowley (1997) claims that word class can explain exceptions to sound change, Donohue (2005) suggests that morphosyntactic structure, that is the distinction between free morpheme and bound morpheme, is more correlated with exceptions to sound change. 2.1.2 Early application vs. late application This subsection gives its attention to morphological conditions and non-exceptions in sound change. Early application and late application mean that morphemes do not undergo a sound change simultaneously: some morphemes undergo it earlier and some morphemes undergo it later. Phillips (1983, 2001, 2006) accounts for this from the perspective of morphological conditions and classifies words into two categories, function words and content words. Function words refer to a wide range of words that normally receive low sentence stress, such as adverbial conjunctions, auxiliary verbs, determiners, prepositions, quantifiers, and so on. Content words mainly include adjectives, adverbs, nouns, verbs, etc. Phillips (1983, 2006) gives an example of strengthening sound change, the change from /d/ to /t/ in Old High German Isidor, and points out that it affected function words last. He (1983, 2006) thus concludes that content words tend to be affected by strengthening sound changes first and function words by weakening sound changes first. Donohue (2005) also tries to explain morphemes leading sound change from the perspective of a morphological condition, but his approach is completely different from that of Phillips (1983, 2001, 2006): Donohue (2005) examines the voicing of voiceless stops in Palu’e and shows that free morphemes tend to lead sound change and bound morphemes follow. Similar to the previous section, disputes are over whether word class or morphosyntactic structure can explain morphemes leading sound change. 2.1.3 Disputes over morphological conditions Though intriguing, the role of morphological conditions in sound change has been challenged by scholars like Jasanoff (1971), Blevins and Lynch (2009), Brown (2013), and so on. Jasanoff (1971) states that what appears to be morphologically conditioned is in fact regular sound change partially obscured by analogy. Blevins and Lynch (2009, p. 111) claim that the sound change discussed in Crowley (1997) applies to all word classes including verbs, but “phonological and morphological aspects of verbal inflectional paradigms” restore the change in verbs later and give rise to “the apparent exceptionality.” Renwick et al. (2014) also focus on word-final /t, d/ deletion in British English as Guy (1991b) and Baranowski and Turton (2020), but they (2014) claim that their results show little support for the role of any specific morphological condition. What is most surprising is that completely opposite conclusions concerning the role of morphological conditions have been drawn from the same phenomenon, word-final /t, d/ deletion in British English. At the same time, some scholars adopt the middle way by claiming that no conclusion can be drawn yet and further investigation is necessary (Sihler, 2000; Campbell, 2013; Manker, 2015). For example, although Manker (2015, p. 287) states that many examples in Phillips (2006) are “actually … influenced by the ‘most common phonetic environment’ where certain word classes happen to be used in the favorable phonetic environment for the change more often,” Manker (2015) does not give any clear cut answers to this issue. Instead, he (2015) suggests that the possibility of sound changes influenced by morphological factors cannot be absolutely ruled out and needs further extensive investigation, a view in line with Sihler (2000), Campbell (2013), etc. To sum up, controversies concerning the morphological condition are twofold. The first controversy is whether it has a role in explaining exceptions to sound change and leading morphemes in sound change. The second one is whether word class or morphosyntactic structure can account for exceptions and leading morphemes. 2.2 Frequency Morphological conditions are not the only factor put forward in previous studies. The frequency factor is perhaps the most widely argued: a long-standing debate exists between scholars claiming that frequency is relevant and others claiming that it is not. What is interesting is that more than a century has passed, and yet there has not been consensus on the frequency effect, and so it is still not well understood. In what follows, this subsection first reviews the frequency effect and exceptions to sound change in previous studies, then reviews the frequency effect and leading morphemes in sound change, and finally reviews disputes over the frequency effect. 2.2.1 Exceptions vs. non-exceptions The frequency effect has been brought to view since the 19th century. Grimm (1822) discusses the relationship between high-frequency auxiliary verbs and their irregularity. Thomsen (1879) gives a few frequent Romanic verbs and the fact that they are exceptions to normal phonetic development. Jespersen ([1922] 2007, p. 267) more plainly expresses Thomsen’s (1879) ideas in English as “words which from their frequent employment are exposed to far more violent changes than other words, and therefore to some extent follow paths of their own.” Vilhelm Thomsen himself gives a similar explanation in his work (Thomsen, 1920). More recently, Labov (1989, p. 44) focuses on Philadelphia a-tensing and reports that “the most common words … show the least tendency to shift to the tense class.” Bermúdez-Otero (2007, p. 512) also states that “the words with the very highest token frequency may exceptionally withstand the change.” Another related research includes Van Bergem (1995). He (1995) discovers that frequency influences the reduction of a pre-stressed vowel in Dutch: the high-frequency words, such as minuut (‘minute’), vakantie (‘holiday’), and patat (‘chips’), are more likely to have a schwa in the first syllable than the phonetically identical low-frequency terms, e.g., miniem (‘marginal’), patent (‘patent’), vakante (‘vacant’). Fidelholtz (1975) reports a similar tendency for the reduction of pre-stressed vowels in English words. In contrast, other studies suggest that low-frequency words tend to be exceptions to sound change. To exemplify, Bybee (2002) studies the deletion of word-final /t/ and /d/ in American English and finds that the deletion rates in low-frequency words are statistically lower than in high-frequency words. Coetzee and Kawahara (2013, p. 62) observe two language phenomena, English t/d-deletion and geminate devoicing in Japanese loanwords, and argue that “t/d-deletion usually applies at higher rates to words of higher frequency,” and frequency and rate of Japanese geminate devoicing are positively correlated. 2.2.2 Early application vs. late application Concerning the frequency effect and leading words in sound change, Hooper (1976) focuses on schwa deletion in English and concludes that frequent words tend to lead this change. Furthermore, Hay and Foulkes (2016) focus on the ongoing change in the pronunciation of word-medial intervocalic /t/ in New Zealand English and report that frequent words lead this change (see also Pierrehumbert, 2001; Duncan, 2011). Not all scholars hold a similar view. To name a few, Hay et al. (2015, p. 83) conclude the study of regular pronunciation changes in New Zealand English over a 130-year period with the expression that “low-frequency words were at the forefront of … changes and higher frequency words lagged behind.” A further dimension of debate is that some scholars claim that different sound changes are led by words of different frequencies. Phillips (1984, 2001, 2006) states that the most frequent words lead sound changes motivated by physiological factors, such as vowel reduction, deletion, assimilation, etc., while the least frequent words lead sound changes that arise from phonological segmental and sequential constraints of the language, such as unrounding in Middle English, diatone formation in Modern English, and others (see also Ogura, 2012). 2.2.3 Disputes over the frequency factor Fruehwald et al. (2013) express their doubt concerning the role of frequency in sound change. They (2013, p. 219) focus on the Middle High German final stop fortition and claim that this change progresses “in frequency in every context at the same rate over time,” the so-called constant rate effect (see also Kroch, 1989, 1994; Pintzuk, 1991; Santorini, 1992, 1993; Dinkin, 2008). Other scholars more plainly claim that sound change is independent of frequency effects. For example, Zellou and Tamminga (2014, p. 18) study the co-articulatory vowel nasality in Philadelphia English and conclude that “the changes in nasality are independent of an observed frequency effect.” Similarly, Labov (2010) examines the role of frequency in several different phonetically gradual changes and gives the conclusion that the role of frequency is minimal, even if not zero, a view agreed on by Kiparsky (2014). Attention has also been paid to language processes which have been used to support the role of frequency in sound change. To exemplify, word-final /t, d/ deletion in American English is used by Bybee (2002) to argue for the role of frequency in sound change as noted in Section 2.2.1. Walker (2012) focuses on word-final /t, d/ deletion in Canadian English, and reports that his initial results show the correlation between frequency and deletion. However, he (2012) further states that only phonological and morphological factor groups have emerged as statistically significant after he considered more factor groups. Abramowicz (2007) suggests that since scholars like Bybee (2002) and Phillips (1983, 2006) have used the variation word-final /t, d/ deletion in English to argue for the role of frequency, it is reasonable to expect the variable ing, that is g-dropping as in walkin’ or livin’, to show similar effects in terms of frequency. However, Abramowicz (2007) concludes that his study does not show much frequency effect. Tamminga (2014, p. 457) argues against the frequency effect from another perspective: he questions the legitimacy of using word-final /t, d/ deletion in English to discuss the role of frequency in sound change since “[t]here has never been any evidence … that coronal stop deletion is a change in progress in any North American dialect.” In other words, Tamminga (2014, p. 457) claims that the data of word-final /t, d/ deletion in English are “stable variation,” but they have been used as evidence for “change in progress.” Tamminga (2014, p. 458) further explores the adjective, conjunction, discourse marker, and preposition forms of like and claims that “frequency effects fail to arise.” 2.3 Present study proposal In sum, disputes in previous studies involve the following two questions. (1) Can morphological conditions and frequency account for exceptions to sound change? (2) Can morphological conditions and frequency account for words leading sound change? If answers to the above two questions are yes, then the following two questions should also be brought forward. (1) In terms of morphological condition, does word class or morphosyntactic structure have a role in sound change? (2) In terms of frequency, do high-frequency words or low-frequency words carry the tendency to be exceptions to sound change, and also, do they tend to lead sound change? To answer all these questions, the present study proceeds step by step; it first compares exceptions with non-exceptions in the diphthongization of [i] to [ei] in Mandarin and then compares words that have led this process with words that have undergone it later. A comparison between exceptions and non-exceptions by the use of statistical analysis may present hints concerning factors to explain exceptions to sound change. A statistical analysis of words leading sound change with those undergoing it later may present factors correlated with words at the forefront of sound change. In addition, the present paper notices a factor that awaits exploration about its role in sound change: previous studies have made little reference to the frequency change factor. The frequency change is calculated by the subtraction of the frequency of a word in the time concerned with the frequency of the same word in an earlier period. If the frequency factor is correlated with sound change, the frequency change factor may also be associated with sound change. To exemplify, Pierrehumbert (2001), Duncan (2011), among others claim that sound change usually affects the most frequent lexical items first. Following their logic, lexical items with increased frequency seem more likely to lead a certain sound change than lexical items with decreased frequency, since lexical items with increased frequency are more active and more accessible to a related sound change than lexical items with decreased frequency. In sum, this paper supposes that the frequency change factor also constitutes a desideratum for research. 3 Diphthongization of [i] to [ei] in Mandarin This paper takes the diphthongization of [i] to [ei] in historical Chinese as its language sample. The diphthongization is a part of the Middle Chinese Great Vowel Shift (Chen 1976, Li 1999), which began no later than the end of the 16th century and finished no later than the beginning of the 19th century (Trigault, [1626] 1957; Edkins, 1857; Luo, 2008). Chart (1) graphically presents the Middle Chinese Great Vowel Shift (Chen, 1976; Li, 1999) (1) The Middl According to Chart (1), the general upward movement pushed the original high vowels *i and *u to undergo diphthongization and “became /.i/ and /.u/ respectively…. Eventually, /.i/ and /.u/ emerged as [ei] and [ou]” (Chen, 1976, p. 194). Due to the limited space, the present paper exclusively focuses on *i. The diphthongization of [i] to [ei] applied with certain conditions. However, diphthongization was “exceptionless with regard to” [i] in the syllables [-ui], [vi], and [fi] in Middle Chinese (AD 601–AD 1336) according to Chen (1976, p. 200). The consonant [v] gradually turned to [u] in the Ming dynasty (1368–1644), almost simultaneously with diphthongization of [i] to [ei] (Luo, 2008). As a result, the three syllables [-ui], [vi], and [fi] in Middle Chinese were “obligatorily realized as [-uei] and [fei] respectively” in Mandarin (AD 1324–Present) (Chen, 1976, p. 200). In other words, the syllables [-ui], [vi], and [fi] are not in the Mandarin syllable inventory. The condition was more complex with [i] in the syllables [bi], [mi], [pi], and [phi] in Middle Chinese (Chen, 1976). Here are some related examples. Table 1: Diphthongization of [i] to [ei] in Mandarin (Baxter & Sagart, 2014) Middle Chinese Mandarin Gloss [fi] [fei] . ‘not’ [gwijH] [ku.e..] . ‘box’ [pjie] [pei] . ‘low, humble’ [pjij] [pi] . ‘cover, protect’ [mijH] [mei] . ‘love, flatter’ [mij] [mi] . ‘a kind of deer’ Historical Chinese is usually divided into the following three phases: Old Chinese (1250 BC–AD 600), Middle Chinese (AD 601–AD 1336), and Mandarin (AD 1324–Present) (Wang, 1957, 1985; Pulleyblank, 1984, 1991; Shi, 2002; Handel, 2015; Pan and Zhang, 2015; Peyraube, 2020; Shen, 2020). All transcriptions of Middle Chinese and Mandarin in this paper are given according to Baxter and Sagart (2014), with reference to Zhongyuan Yinyun (Rhymes of the Central Plain; Zhou, [1324] 1996) and reconstructions of Zhongyuan Yinyun in Pulleyblank (1984, 1991) and Chou (1993). Tone marks are omitted since they are irrelevant to the present study. As shown in Table 1, [i] in the syllables [fi] and [gwijH] was diphthongized to [ei] in Mandarin. However, [i] in the syllables [bi], [mi], [pi], and [phi] has a more complicated pattern. To exemplify, the two morphemes ‘low, humble’ (. [pjie]) and ‘cover, protect’ (. [pjij]) have similar pronunciations in Middle Chinese, but they have different pronunciations in Mandarin: the morpheme ‘low, humble’ has been diphthongized into [pei], while the morpheme ‘cover, protect’ remains [pi]. Similarly, [i] in the morpheme ‘love, flatter’ (. [mijH]) in Middle Chinese is realized as [ei] in Mandarin, while [i] in the morpheme ‘a kind of deer’ (. [mij]) remains [i] in Mandarin. Chen (1976) suggests that diphthongization of [i] in the syllables [bi], [mi], [pi], and [phi] is a highly irregular process in the sense that neither manner of articulation of the bilabial initials, prosodic features, nor fine distinctions among these syllables in Middle Chinese could explain why [i] has been diphthongized into [ei] in some syllables, while has remained [i] in other syllables. In the next section, statistical analysis is used to locate factors to account for these exceptions to diphthongization of [i] to [ei], i.e., those morphemes that remain [i] in Mandarin. 4 Exceptions vs. non-exceptions The paper firstly relies on Baxter and Sagart (2014), with reference to Zhongyuan Yinyun (Rhymes of the Central Plain; Zhou, [1324] 1996) and reconstructions of Zhongyuan Yinyun in Pulleyblank (1984, 1991) and Chou (1993), to locate morphemes of [fi], [-ui], [vi], [bi], [mi], [pi], and [phi] in Middle Chinese. Then the paper uses the CCL Corpus (Center for Chinese Linguistics PKU) to look for related information concerning both morphemes that have been diphthongized into [-ei] and those that remain [-i] in Mandarin. The CCL Corpus is composed of two databases: an Old Chinese and Middle Chinese database and a Modern Mandarin database. It also permits searching for data according to Chinese dynasties. Another benefit of the corpus is its capacity, over 470 million Chinese characters from a wide range of sources. Diphthongization of [i] to [ei] began no later than the end of the 16th century and finished no later than the beginning of the 19th century (Chen, 1976; Luo, 2008; Shen, 2020). As the time phase of diphthongization was mainly within the Qing dynasty (1644–1912), data from the Qing dynasty were extracted. In addition, data from the Ming dynasty (1368–1644) were also extracted to calculate frequency change from the Ming dynasty to the Qing dynasty. Altogether this paper locates 201 related morphemes after the exclusion of obsolete morphemes. Among them, 109 morphemes have been diphthongized to [ei] in Mandarin, and 92 morphemes remain [i] in Mandarin. The factors for statistical analysis, their respective factor levels, and statistical analysis results are reported below in Table 2. Table 2: Data and results for the binary logistic regression model (exceptions vs. non-exceptions) Factor Factor Estimate Std. |z| p Intercept 2.46 0.34 7.17 <0.00 * Morphosyntactic structure (1644–1912) Free Bound 0.27 0.43 1.21 0.63 Word class (1644–1912) Function Content -1.37 0.91 1.50 0.79 Normalized frequency (1644–1912) Numerical -0.00 0.00 0.13 0.90 Frequency dummy (1644–1912) Low Medium High -0.08 0.04 1.96 0.04 * Frequency change from between 1368 and 1644 to between 1644 and 1912 Numerical -0.14 0.46 0.73 0.12 Frequency change from between 1368 and 1644 to between 1644 and 1912 dummy Decrease Increase -0.17 0.38 0.46 0.65 Notes: * = p < 0.05. |z| stands for the absolute value of z as given in the GraphPad Prism version 8.0.0 for Windows. 4.1 Factors and factor levels in Table 2 As stated in Section 2.1.1, Donohue (2005) claims sound change advances in bound grammatical morphemes more completely than in free lexemes. Bybee (2002), Guy (1991b), Baranowski and Turton (2020), among others, claim that bound morphemes can affect /t, d/ deletion in English. Thus, the factor of morphosyntactic structure (1644–1912) with two levels free and bound was constructed to test whether the morphosyntactic structure has a role in the sound change. The time period 1644–1912 means that the data were extracted from the language dating to the Qing dynasty (1644–1912). Free and bound respectively mean that a related morpheme is mainly used either as a free or as a bound morpheme. “If a morpheme can stand alone in an utterance to represent a … part of speech …, it is free. If it must be augmented with additional language material …, it is bound” (Packard, 2015, p. 264; see also Chao, 1968; Hsieh, 2016). To exemplify, the morpheme ‘love, flatter’ (.) in Table 1 is a free morpheme because it can represent an adjective, while the morpheme ‘box’ (.) is a bound morpheme since it must be used with another morpheme in a word. The factor of word class (1644–1912) with two levels, namely the content and the function was configured to examine the contradictory claims concerning the role of word classes in the sound change discussed in Crowley (1997), Blevins and Lynch (2009), and others in Section 2.1.3. Adjectives, nouns, verbs, etc., are classified as content words; adverbial conjunctions, auxiliary verbs, determiners, prepositions, quantifiers, etc are classified as function words, which is in line with the dichotomy of words in Phillips (1983, 2001, 2006). It may appear ideal to classify words into adjectives, adverbial conjunctions, determiners, nouns, prepositions, verbs, etc, however, for statistical analysis, we shall avoid too many factor levels. As noted in Section 2.2.1, the frequency factor is claimed to be associated with exceptions to sound change by some scholars, although disagreement exists concerning whether high-frequency words or low-frequency words lead sound changes (Grimm, 1822; Bybee, 1985, 2000, 2002; Pierrehumbert, 2001; Bermúdez-Otero, 2007; Smith, 2012; Hay and Foulkes, 2016). The raw numerical data of frequency between 1644 and 1912 were examined in the first place. The cross-tabulation analysis carried out on the GraphPad Prism version 8.0.0 for Windows (hereafter the GraphPad software) revealed that it was rejected as a statistically significant factor for diphthongization (p = 0.63). Thus the raw data of frequency between 1644 and 1912 were normalized on the GraphPad software and reported as normalized frequency (1644–1912) in Table 2. The factor of frequency dummy (1644–1912) was configured following the debate in Section 2.2 concerning whether low-frequency words or high-frequency words lead sound changes. It was also partly configured in line with claims in Wedel et al. (2013) and Liu (n.d.). Wedel et al. (2013) claim that the relative frequency of minimal pair members, instead of the absolute frequencies, is a significant predictor of phoneme merger. Liu (n.d.) compares the relative frequencies of all morphemes involved in palatalization in Mandarin and finds that relative frequency is statistically significantly correlated with it. The present study does not refer to pair members and thus does not refer to the relative frequency of pair members. Instead, the present study refers to all morphemes involved in diphthongization. Therefore, it took into account the relative frequencies of all related morphemes following Liu (n.d.). The factor frequency dummy (1644–1912) has three factor levels: low, medium, and high. Each level takes one-third of the data: one-third of the data with the lowest frequencies in this column is marked as low; another one-third with the highest frequencies is marked as high; the remaining one-third between low and high is medium. As a result, low here does not refer to a frequency lower than a specific count. Instead, it means that the frequency of a certain morpheme is among the lowest frequencies of all morphemes involved in the diphthongization of [i] to [ei]. The next factor, namely the frequency change from between 1368 and 1644 to between 1644 and 1912 (henceforth frequency change) was introduced due to the possibility that morphemes with either increased or decreased frequencies may have undergone diphthongization at different rates. For example, the frequency of the morpheme ‘not’ (. [fei]) in Table 1 is 5633 in the period from 1368 to 1644 and 14457 in the period from 1644 to 1912. Thus the frequency change for the morpheme ‘not’ (. [fei]) is 8824, where the positive number means that comparing the first and the second period, its frequency has increased. It is possible to normalize the raw data of frequency change by adding all numbers with the absolute of the most negative. In this way, the most negative number will become zero, and all the other numbers become positive. However, the focus of the frequency change factor is partly on whether related morphemes have increased or decreased frequency. Therefore, the present study will use raw data instead of normalized data. The factor of frequency change from between 1368 and 1644 to between 1644 and 1912 dummy (hereafter frequency change dummy) was introduced because it seems that whether frequency has decreased or increased is also a factor in sound change. The raw numerical data for the above factor frequency change were converted to categorical data with two levels: decrease and increase, with decrease as the reference level. The morpheme ‘not’ (. [fei]) in Table 1 is exemplified again: its frequency increased 8824 times from between 1368 and 1644 to between 1644 and 1912, so it is marked as an increase for the factor of frequency change dummy. 4.2 The binary logistic regression results The statistical relationship between the six factors in Table 2 and the dependent variable diphthongization of [i] to [ei] was assessed using multiple logistic regression in the GraphPad software. Model selection was guided by AIC (Akaike Information Criterion; Akaike, 1974; Burnham and Anderson, 2004), calculated probability (p-value), and VIF (Variance Inflation Factor; Rawlings et al., 1998; James et al., 2017). The dependent variable has two categories: undiphthongized and diphthongized, with undiphthongized as the reference level. Undiphthongized means that a related morpheme remains [i] in Mandarin, while diphthongized means that a relevant morpheme has been diphthongized to [ei]. A p-value smaller than 0.05 was considered statistically significant. As shown in Table 2, the frequency dummy (1644–1912) is the only factor that has emerged as statistically significant (p = 0.04). Its negative coefficient indicates that the possibility of undergoing diphthongization decreases from the low level, medium level, to the high level (Estimate = -0.08). In other words, the higher the frequency of a morpheme is, the less likely for it to undergo diphthongization. Morphemes with the highest frequencies tend to be exceptions to diphthongization. Other factors like morphosyntactic structure, word class, and frequency change have been rejected as statistically significant. 5 Early application vs. late application This section considers the morphemes that have been diphthongized to [ei] in Mandarin to explore factors that account for morphemes leading this sound change process. 5.1 Data source This paper relies on works compiled at the beginning of diphthongization to look for morphemes that were at the forefront of this process and then carries out statistical analysis. It may seem that works compiled by Chinese scholars in the 17th century are the best choice since diphthongization began no later than the end of the 16th century (Chen, 1976; Luo, 2008; Shen, 2020). However, the choice is not as straightforward as it appears to be: dictionaries and books compiled by Chinese scholars before the 20th century use fanqie (..), a traditional method of indicating the pronunciation of a Chinese character by using two other Chinese characters. For example, the pronunciation of the character . might be represented as the following: ... It roughly means that the initial of . is the same as that of ., and the final of . is the same as that of .. This representation makes it circular and thus difficult to understand the pronunciations of characters and morphemes they represent since the Chinese writing system is a representative logographic system, not a phonographic system like English. In contrast, dictionaries compiled by missionaries to China use a Romanization system and can provide a relatively clear picture of the pronunciation of Mandarin during the time concerned. Aid to the Eyes and Ears of Western Literati (Xiruermuzi; Trigault, [1626] 1957) is a dictionary that contains the first Romanization system of the Chinese written language, and is an essential guide to the pronunciation of Chinese characters (Wang, 2016; Li, 2020). As noted in Section 4, this paper locates 201 morphemes related to the diphthongization of [i] to [ei]. In this section, we focus solely on the 109 morphemes that have been diphthongized to [ei] in Mandarin. The paper uses Aid to the Eyes and Ears of Western Literati (Trigault, [1626]1957) to locate morphemes that were at the forefront of diphthongization of [i] to [ei]. Then the paper uses the CCL corpus to look for related information concerning all the 109 morphemes and locate factors in morphemes leading the diphthongization. 5.2 Statistical analysis results: early application vs. late application The dictionary Aid to the Eyes and Ears of Western Literati (Trigault, [1626] 1957) was compiled during the time of the Ming dynasty (1368–1644). Accordingly, the focus of this research is on the data from the Ming dynasty, and frequency change is assumed to be a factor in sound change. To be able to calculate the frequency change, the data related to frequency that came before the Ming dynasty is needed. The Ming dynasty was preceded by the Yuan dynasty (1271–1368). However, the Yuan dynasty lasted for less than one hundred years and there is little data to work on. As a result, this study extracted data from both the Yuan dynasty and the Southern Song dynasty (1127–1279). To simplify it for readers who are unfamiliar with Chinese history, the paper henceforth refers to frequency change from the Southern Song and Yuan dynasties to the Ming dynasty as frequency change from between 1127 and 1368 to between 1368 and 1644. The data and statistical analysis results are shown in Table 3. Table 3: Data and results for the binary logistic regression model (early application vs. late application) Factor Factor Estimate Std. |z| p Intercept -0.69 0.215 4.10 0.02 * Normalized frequency (1368–1644) Numerical 0.01 0.01 1.37 0.21 Frequency dummy (1368–1644) Low Medium High 0.09 0.02 1.98 0.03 * Frequency change from between 1127 and 1368 to between 1368 and 1644 Numerical 0.61 0.27 1.34 0.15 Frequency change from between 1127 and 1368 to between 1368 and 1644 dummy Decrease Increase 0.52 0.28 1.89 0.04 * Notes: * = p < 0.05. |z| stands for the absolute value of z as given in the GraphPad software. The raw data of frequency (1368–1644) does not show the normal distribution and were thus normalized on the GraphPad software, and reported as normalized frequency (1368–1644). The binary logistic regression analysis carried out on the GraphPad software revealed that the factors of frequency dummy (1368–1644) and frequency change from between 1127 and 1368 to between 1368 and 1644 dummy have statistically significant correlation with morphemes leading diphthongization of [i] to [ei] (p = 0.03, 0.04). The positive value of the coefficient of frequency dummy (1368–1644) suggests that this factor has an additive effect on diphthongization (Estimate = 0.09): the possibility of leading diphthongization increases from the low level, medium level, to the high level of frequency dummy (1368–1644). In a similar vein, the positive value of the coefficient of frequency change from between 1127 and 1368 to between 1368 and 1644 dummy indicates that a morpheme that has an increased frequency tends to undergo diphthongization first (Estimate = 0.52). To sum up, the two factors to account for morphemes leading diphthongization of [i] to [ei] are frequency and frequency change. 5.3 Frequency: exceptions vs. early application Another statistical analysis was carried out to examine differences between the frequencies of the exceptional morphemes to diphthongization of [i] to [ei] in the time frame of 1644 to 1912 and the frequencies of the leading morphemes in the time frame of 1368 to 1644. The two sets of data were firstly normalized on the GraphPad software. A Mann-Whitney test carried out on the same software shows that statistically significant differences exist between the two sets of data (p = 0.04). Descriptive statistical analysis of the raw data was also carried out on the GraphPad software. The mean frequency of the exceptional morphemes is 926.8, while the mean frequency of the leading morphemes is 658.3. The highest frequency of the exceptional morphemes is 8229, while the highest frequency of the leading morphemes is 5662. Both the mean frequency and the highest frequency of the exceptional morphemes are about 1.4 times higher than those of the leading morphemes. The present study cannot draw any conclusions on whether the multiple of 1.4 may be universal or whether it changes from one sound change process to another. To do so, more sound change processes within one language as well as sound processes across languages need to undergo the analyses. The topic proves to be a boon for later research. 6 Conclusion Word class and morphosyntactic structure, or morphological condition in a broader term, have been rejected as statistically significant both in accounting for exceptions to diphthongization and leading morphemes in diphthongization. This suggests that morphological condition does not have a role in diphthongization. Previous studies mainly focus on whether high-frequency morphemes or low-frequency morphemes lead sound change. The present study reveals that the role of the frequency factor in sound change is more complex than the debate in previous studies. The frequency factor has been proven as statistically significant both for exceptions to diphthongization of [i] to [ei] and leading morphemes in it. What proved interesting is the following two points: (1) high-frequency morphemes tend to be exceptions to diphthongization; (2) among morphemes that underwent diphthongization, high-frequency morphemes tend to lead diphthongization. More plainly, morphemes with the highest frequency tend to be exceptions to diphthongization. High-frequency morphemes among non-exceptional morphemes tend to lead diphthongization, although the frequencies of these high-frequency morphemes tend to be less than the frequencies of exceptional morphemes. Another statistically significant factor to explain leading morphemes in diphthongization is frequency change: a morpheme that has an increased frequency tends to undergo diphthongization earlier. This factor has not emerged as statistically significant to account for exceptions to diphthongization. Put differently, frequency change is not correlated with exceptions to diphthongization but correlated with early application of diphthongization. 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Keywords: prosodic typology, features, pitch-accent languages, Japanese, Slovene Povzetek Clanek na kratko opisuje zgodovinski razvoj prozodicne tipologije jezikov, predstavi dva prozodicna prototipa na besednem nivoju, ki ju je predlagal Hyman, in pojasnjuje položaj tonemskih jezikov na leksikalnem nivoju. Opozarja na lažno podobnost japonšcine in slovenšcine, ki je nastala z uvedbo znacilnosti [±kulminativen], in predlaga njeno razširitev s funkcijo [±eliminativ], ki foneticno utemeljuje razliko med tonemskimi sistemi in jakostno-naglasnim prototipom. Kljucne besede: prozodicna tipologija, razlocevalne lastnosti, tonemski jeziki, japonšcina, slovenšcina 1 Introduction Prosodic typology classified world languages by setting two opposite prototypes, tone languages such as Cantonese, Yoruba, etc. with the feature [+tonal] and stress languages such as English, Turkish, etc. with the feature [.tonal]. In the history of prosodic research, research on tone languages and their prototype progressed quickly and successfully implemented the binary tonal distinction high (H) and low (L) on each segment, leaving out the so-called pitch-accent languages. Stress on the other hand was phonetically elusive and was considered a mental construct. The already marginal phonological status of stress was weakened even further when the binary tone system proved to be applicable for intonation studies. This approach blurred pitch-accent languages such as Japanese, Swedish, etc. with stress languages because they share a common property; that is the feature [+culminative] also called accent. Intonation phonology became the means of comparison among languages. The ToBI models, the transcription and annotation tools of prosodic events which would include both intonation and voice flow segmentation in units of study, define whether languages differ in the types of tones or/and tonal inventories they have, and consequently devide languages to tone languages, accent languages, and languages with no lexical specification of prosody. Though ToBI models are indispensable in computer technology, which requires automated analysis of large speech corpora annotated with standardized annotation strings, Jun (2005, p. 437) points out that comparisons of prosodic systems based on phonetic descriptions show certain limitations. One very important limitation is that the similarities shown in the surface realization do not guarantee the same underlying distinctive prosodic features or structures and may be entirely accidental (also Gussenhoven, 2007; Ladd, 2008 [1996]; Hyman, 2011). The types of tones cannot distinguish stress-accent languages from lexical pitch-accent languages because the autosegmental-metrical model (AM model) does not specify whether pitch accent is a lexical property or a postlexical property. As an example of such coincidence, Gussenhoven (2007, p. 256) points at the surface similarity between English and Tokyo Japanese H*L to write that ‘while phonologically comparable, the pitch accents of Japanese and English have very different morphological statuses’. In Japanese, they form part of the underlying phonological specification of morphemes, along with the vowels and consonants. In English, on the other hand, pitch accents are intonational and therefore morphemically independent of the words they come with, and are chiefly used to express the information status of the expression. Closely related to this is also the false similarity of surface representations of different accent patterns in declarative intonation presented for Japanese and Slovene (Golob, 2011). Therefore, this research will return to the so-called broad-stroke typology, where phonological systems are treated level-ordered, cf. the prosodic property of an utterance is a combination of prosody at the lexical level and prosody at the post-lexical level, with the former constraining the latter and the latter including the prosodic features of the former. The structural approach, where there is a clear distinction between word-level tones and stress at the lexical level, is indispensable for practically any interdisciplinary research involving accounting for the structural properties of phonological systems (and their interface with morphology and syntax), predicting the effects that stress (but not tone) can have on segments, tracing linguistic change, conducting fieldwork on understudied and endangered languages, and last but not least, explaining foreign accents in second language acquisition. 2 Structural approach to prosody and difficulties in L2 acquistion Foreign accents in second language production are caused by interference from the phonological system and phonetic realization of the speaker’s first language. Within the area of prosody, several studies have reported that lexically linked prosodic features in L1 are more likely to be transferred to L2 prosody and are more difficult to suppress than the post-lexical ones (Jun & Oh, 2000; Ueyama, 2000; Mennen, 2007; Golob, 2021). Furthermore, sudden changes at the paralinguistic level of L2 speech, such as the inclusion of prosodic focus or the use of emotional speech is reported to destroy the already correctly adopted lexical or intonational prosody (Golob, 2008; van Maastricht et al. 2016; Kim, 2018). The above findings show that processes that contribute to the foreign-accentedness in second language production can best be explained level-ordered or in other words, through the recognition of the properties involved at different prosodic levels and their mutual interactions. 3 The aim of this study From teaching experience to Slovene students of Japanese as well as based on the findings about foreign accents in second language production, this study will introduce and evaluate the present word-prosodic typology proposed by Hyman (2006, 2009) through the results of a large acoustic survey that was recently conducted by Golob (2021). 4 Word-prosodic typology Prosodic properties conveyed in an utterance are a combination of prosodic features at the word level and those at the phrase level and that postlexical prosody is constrained by the lexical prosody, and postlexical prosodic information contains information about the lexical prosody. Prosodic typology revisited its foundations (word-prosodic typology) to redefine stress-accent prototype by the properties that would describe both the underlying distinctive prosodic features and their organization. Hyman (2006, p. 231) proposed an additional [+obligatory] saying that stress-accent languages meet the following two central criteria: 11. obligatoriness: every lexical word has at least one syllable marked for the highest degree of metrical prominence (primary stress); 12. culminativity: every lexical word has at most one syllable marked for the highest degree of metrical prominence. By setting the stress language prototype more clearly, classification of languages according to the properties of their subsystems became more straightforward. Pitch-accent systems convey the features [.obligatory] and [+culminative], and based on numerous researches Hyman reckons them as ‘mixed, ambiguous, and sometimes analytically indeterminate systems’ that do not constitute a coherent prosodic type but instead ‘freely pick-and-choose properties from the tone and stress prototypes’ (Hyman, 2009, p. 213). Figure 1: Word-prosodic typology according to Hyman (taken from Golob, 2021, p. 20) The basic distinction [±obligatory] satisfies the difference between Tokyo Japanese as a pitch-accent language and a variation of Standard Slovene as a stress-accent language. Both languages convey the features [+culminative]. Tokyo Japanese is known as a typical pitch-accent or non-stress language in the literature as opposed to a stress-accent language like English (McCawley, 1978; Beckman, 1986). It is also classified as a word-pitch language as opposed to a ‘tone language’ like Mandarin Chinese or an intonation language like English (Pike, 1948). It carries a distinctive lexical pitch accent, which is marked phonetically by the tonal change from H to L (Pierrehumbert & Beckman, 1988; Kubozono, 2008). Tokyo Japanese accent/tone is culminative, a property it shares with stress-accent systems. However, the lexicon is divided into tonic words (accented type) with H-L tonal change and atonic words (unaccented type) that convey no such H-L change. In other words, any given word in theory gets n+1 accent possibilities, n being equal to the number of full moras, tone-bearing units in Tokyo Japanese (Labrune, 2012). (1) ‘pillow’+nom. ‘heart’+nom. ‘mirror’ ‘fish’ a. accentual ma.kura ga koko.ro ga kagami. ga sakana ga b. tonal MAkura ga H L koKOro ga H L kagaMI ga H L sakana ga Some major Japanese dialects are reported to deviate from the standard pitch accent, mainly differing in the number of tonal patterns involved, and few of them are accentless (Uwano, 1999; Kubozono, 2012) Just as Tokyo Japanese was the base for the so-called standard language, Standard Slovene was also constructed upon dialects. There are two prosodically distinct dialect types, the tonal or pitch-accent Slovene and the non-tonal or stress-accent Slovene (Toporišic, 2004 [1976]; Šuštaršic & Tivadar, 2001). The pitch-accent Slovene has distinctive tones, namely the acute (a long rising tone) and the circumflex (a long falling tone) that appear on long stressed vowels. In the absence of a long vowel stress falls on the final syllable still carrying tones. Fixed stress is the norm in Slovene. It is obligatory on every lexical word. In stress-accent Slovene stressed syllable is prominent in the sense that it is longer and conveys higher tone and greater dynamics compared to unstressed syllables (Lehiste, 1970; Bhaskararao & Golob, 2006). (2) ‘saussage’ ‘cupboard’ a. accentual klo*bása o*mâra b. tonal klobasa L H omara H L In overall, the three standard languages, the Tokyo pitch-accent Japanese, the pitch-accent Slovene, and the stress-accent Slovene are described with the following prosodic features according to Hyman’s word-prosodic typology. Figure 2: Japanese and Slovene according to Hyman's word-prosodic typology According to Figure 2, by introducing the feature [±obligatory] the three language systems became prosodically distinct, which, from the point of view of phonology, could be completely satisfactory. However, the feature [±obligatory] alone does not make it possible to understand the prosodic typological differences between the two languages. It seems that it is not directly applicable neither to prosodic function nor to the nature of the stress language prototype, and would only partially or not at all help explain processes that appear during seond language acquisition. In the following section, we will therefore introduce a bidirectional Japanese – Slovene L1 and L2 study that was conducted by Golob (2021), and of which acoustic measurements indicate a prosodic property of a stress-accent language, which is very obvious and is a current topic in phonetic research, but has been overlooked in discussions on prosodic typology features. 5 Stress language prototype revisited: the feature [±eliminative] Golob (2021) conducted an acoustic experiment on Japanese and Slovene as native languages (L1) to show that, although the [+culminative] feature is common to both languages, there is a difference in the parameters responding to it as well as the way they respond. Furthermore, based on the “Integrated Contrastive Model” (Rasier & Hiligsmann, 2007) she observes how acoustic parameters respond to the feature [+culminative] in Japanese and Slovene as second languages (L2) to show that the prosodic mechanism at the word level is the most uncompromising in a language that establishes the overall prosodic circumstance. Measured acoustic parameters, namely vowel formants, duration, fundamental frequency, and intensity match the four prosodies reported by Pfitzinger (2006), thought to be essential for the linguistic aspect of prosody (vs. para-linguistic, extra-linguistic). In general, the results for L1 Japanese and L1 Slovene show clear trends and support previous results. They serve as the benchmark for the L2 Japanese and L2 Slovene results and point out some new and interesting trends. In L1 Japanese, pitch is the only prosodic feature that shows a systemic and uniform response, namely that accented vowels have a statistically higher pitch than the following vowels. In L1 Slovene, on the other hand, the pitch showed violent reactions but due to unclear tendencies, we consider it to be strongly structured. In other words, we assume that factors at higher metrical levels influence acoustic pitch values. The other three parameters in L1 Slovene show uniform responses; accented vowels are statistically longer than the following vowels, they show no apparent vowel reduction compared to the unaccented vowels, and they are statistically pronounced with higher intensity than the following vowels. The intensity response was rated as less reliable, with data showing statistical significance in three out of five informants. Results for the second languages provide further important insights. L2 Japanese shows no correspondence to the [+culminative] feature, the deviation in the acoustic data is negligible for all speakers. On the other hand, L2 Slovene shows much more prosodic activity. The pitch showed violent responses as in L1 Slovene but the trend is unclear and requires further investigation. On the other hand, vowel formants are the only parameter that does not respond to the [+culminative] feature, and no vowel reduction is observed. In this context, the L2 Slovene manifestation of the duration response deserves further attention. Four out of five informants showed statistically greater duration on accented vowels and at the same time no vowel reduction, suggesting that Japanese speakers of Slovene used the segmental long-short distinction found in their native language to respond to the [+culminative] feature. The above results suggest that the interpretation of word-level syntagmatic prominence in the case of stress language prototype needs to be reconsidered, and as suggested, should be defined bidirectionally. To rephrase, a part of a phonological word is prominent, either because the parameters of the outstanding part are in some way superiorized compared to those of the rest of the word (maximizing the paradigmatic opposition), or because the parameters of the rest of the word are in some way inferiorized (minimizing the paradigmatic opposition), or both. The [+culminative] feature represents the former process, namely the superiorization of one part of a phonological word. As for the minimalization process to fulfill the insufficiency with the conventional typological features, Golob (2021) proposed a new prosodic typological feature called [±eliminative], the actual prosodic role of which should yet be investigated. References Beckman, M. E. & Pierrehumbert, J. B. (1986). 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