Search results for: syntactic parsing

Authors: Lesley Karen Penera

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Despite the countless that has been drawn to investigate Philippine English for a myriad of reasons, none was known to have ventured on a probe of its grammatical features as used in a technology-driven linguistic landscape by two generations in the digital age. Propelled by the assumption of an emerging Philippine English variety, this paper determined the grammatical features that characterize the digital native-immigrants’ Philippine English. It also ascertained whether mistake or deviation instigated the use of the features, and established this variety’s level of comprehensibility. This exploratory mixed-methods inquiry employed some qualitative and quantitative data drawn from a social networking site, the digital native-immigrant group, and the comprehensibility-raters who were selected through non-random purposive sampling. The study yields 8 grammatical features, mostly deemed results of deviation, yet the texts characterized by such features were mostly rated with excellent comprehensibility. This substantiates some of the grammatical features identified in earlier studies, provides evidentiary proof that the digital groups’ Philippine English is not bound by the standard of syntactic accuracy and corroborates the assertion on language’s manipulability as an instrument fashioned to satisfy the users’ need for successful communication in actual instances for use of English past the walls of any university where the variety is cultivated. The same could also be rationalized by some respondents’ position on grammar and accuracy to be less vital than one’s facility to communicate effectively.

Keywords: comprehensibility, deviation, digital immigrants, digital natives, mistake, Philippine English variety

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Authors: Aliaksandr Huminski

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Semantic Role Labeling (SRL) as shallow semantic parsing approach includes recognition and labeling arguments of a verb in a sentence. Verb participants are linked with specific semantic roles (Agent, Patient, Instrument, Location, etc.). Thus, SRL can answer on key questions such as ‘Who’, ‘When’, ‘What’, ‘Where’ in a text and it is widely applied in dialog systems, question-answering, named entity recognition, information retrieval, and other fields of NLP. However, SRL has the following flaw: Two sentences with identical (or almost identical) meaning can have different semantic role structures. Let consider 2 sentences: (1) John put butter on the bread. (2) John buttered the bread. SRL for (1) and (2) will be significantly different. For the verb put in (1) it is [Agent + Patient + Goal], but for the verb butter in (2) it is [Agent + Goal]. It happens because of one of the most interesting and intriguing features of a verb: Its ability to capture participants as in the case of the verb butter, or their features as, say, in the case of the verb drink where the participant’s feature being liquid is shared with the verb. This capture looks like a total fusion of meaning and cannot be decomposed in direct way (in comparison with compound verbs like babysit or breastfeed). From this perspective, SRL looks really shallow to represent semantic structure. If the key point in semantic representation is an opportunity to use it for making inferences and finding hidden reasons, it assumes by default that two different but semantically identical sentences must have the same semantic structure. Otherwise we will have different inferences from the same meaning. To overcome the above-mentioned flaw, the following approach is suggested. Assume that: P is a participant of relation; F is a feature of a participant; Vcp is a verb that captures a participant; Vcf is a verb that captures a feature of a participant; Vpr is a primitive verb or a verb that does not capture any participant and represents only a relation. In another word, a primitive verb is a verb whose meaning does not include meanings from its surroundings. Then Vcp and Vcf can be decomposed as: Vcp = Vpr +P; Vcf = Vpr +F. If all Vcp and Vcf will be represented this way, then primitive verbs Vpr can be considered as a canonical form for SRL. As a result of that, there will be no hidden participants caught by a verb since all participants will be explicitly unfolded. An obvious example of Vpr is the verb go, which represents pure movement. In this case the verb drink can be represented as man-made movement of liquid into specific direction. Extraction and using primitive verbs for SRL create a canonical representation unique for semantically identical sentences. It leads to the unification of semantic representation. In this case, the critical flaw related to SRL will be resolved.

Keywords: decomposition, labeling, primitive verbs, semantic roles

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Authors: Sophie Whittle

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Prior to present day, English syntax historically exhibited an inconsistent verb-second (V2) rule, which saw the verb move to the second position in the sentence following the fronting of a type of phrase. There was a high amount of variation throughout the history of English with regard to the ordering of subject and verb, and many explanations attempting to account for this variation have been documented in previous literature. However, these attempts have been contradictory, with many accounts positing the effect of previous syntactic changes as the main motivations behind the decline of V2. For instance, morphosyntactic changes, such as the loss of clitics and the loss of empty expletives, have been loosely connected to changes in frequency for the loss of V2. The questions surrounding the development of non-V2 in English have, therefore, yet to be answered. The current paper aims to bring together a number of explanations from different linguistic fields to determine the factors driving the changes in English V2. Using historical corpus-based methods, the study analyses both quantitatively and qualitatively the changes in frequency for the history of V2 in the Old, Middle, and Modern English periods to account for the variation in a range of sentential environments. These methods delve into the study of information structure, prosody and language contact to explain variation within different contexts. The analysis concludes that these factors, in addition to changes within the syntax, are responsible for the position of verb movement. The loss of V2 serves as an exemplar study within the field of historical linguistics, which combines a number of factors in explaining language change in general.

Keywords: corpora, English, language change, mixed-methods, syntax, verb-second

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Authors: Jelena Radmanovic

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On 5 March 2020, the International Criminal Court has decided to authorize the investigation into the crimes allegedly committed on the territory of Afghanistan after 1 May 2003. The said determination has raised several controversies, including the recently imposed sanctions by the United States, furthering the United States' long-standing rejection of the authority of the International Criminal Court. The purpose of this research is to address the said investigation in light of its importance for the prevention of impunity in the cases where the perpetrators are nationals of Non-Party States to the Rome Statute. Difficulties that the International Criminal Court has been facing, concerning the establishment of its jurisdiction in those instances where an involved state is not a Party to the Rome Statute, have become the most significant stumbling block undermining the importance, integrity, and influence of the Court. The Situation in Afghanistan raises even further concern, bearing in mind that the Prosecutor’s Request for authorization of an investigation pursuant to article 15 from 20 November 2017 has initially been rejected with the ‘interests of justice’ as an applied rationale. The first method used for the present research is the description of the actual events regarding the aforementioned decisions and the following reactions in the international community, while with the second method – the method of conceptual analysis, the research will address the decisions pertaining to the International Criminal Court’s jurisdiction and will attempt to address the mentioned Decision of 5 March 2020 as an example of good practice and a precedent that should be followed in all similar situations. The research will attempt parsing the reasons used by the International Criminal Court, giving rather greater attention to the latter decision that has authorized the investigation and the points raised by the officials of the United States. It is a find of this research that the International Criminal Court, together with other similar judicial instances (Nuremberg and Tokyo Tribunals, The International Criminal Tribunal for the former Yugoslavia, The International Criminal Tribunal for Rwanda), has presented the world with the possibility of non-impunity, attempting to prosecute those responsible for the gravest of crimes known to the humanity and has shown that such persons should not enjoy the benefits of their immunities, with its focus primarily on the victims of such crimes. Whilst it is an issue that will most certainly be addressed further in the future, with the situations that will be brought before the International Criminal Court, the present research will make an attempt at pointing to the significance of the situation in Afghanistan, the International Criminal Court as such and the international criminal justice as a whole, for the purpose of putting an end to impunity.

Keywords: Afghanistan, impunity, international criminal court, sanctions, United States

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Authors: Tayebeh Norouzi

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This study aims to investigate the acquisition process of intonation. It examines the intonation structure of Tokyo Japanese and its realization by Iranian learners of Japanese. Seven Iranian learners of Japanese, differing in fluency, and two Japanese speakers participated in the experiment. Two sentences were used to test the phonological and phonetic characteristics of lexical pitch-accent as well as the intonation patterns produced by the speakers. Both sentences consisted of similar words with the same number of syllables and lexical pitch-accents but different syntactic structure. Speakers were asked to read each sentence three times at normal speed, and the data were analyzed by Praat. The results show that lexical pitch-accent, Accentual Phrase (AP) and AP boundary tone realization vary depending on sentence type. For sentences of type XdeYwo, the lexical pitch-accent is realized properly. However, there is a rise in AP boundary tone regardless of speakers’ level of fluency. In contrast, in sentences of type XnoYwo, the lexical pitch-accent and AP boundary tone vary depending on the speakers’ fluency level. Advanced speakers are better at grouping words into phrases and produce more native-like intonation patterns, though they are not able to realize downstep properly. The non-native speakers tried to realize proper intonation patterns by making changes in lexical accent and boundary tone.

Keywords: intonation, Iranian learners, Japanese prosody, lexical accent, second language acquisition.

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Authors: Saad M. Darwish, Magda M. Madbouly, Murad B. Khorsheed

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Sign Languages (SL) are the most accomplished forms of gestural communication. Therefore, their automatic analysis is a real challenge, which is interestingly implied to their lexical and syntactic organization levels. Hidden Markov models (HMM’s) have been used prominently and successfully in speech recognition and, more recently, in handwriting recognition. Consequently, they seem ideal for visual recognition of complex, structured hand gestures such as are found in sign language. In this paper, several results concerning static hand gesture recognition using an algorithm based on Type-2 Fuzzy HMM (T2FHMM) are presented. The features used as observables in the training as well as in the recognition phases are based on Singular Value Decomposition (SVD). SVD is an extension of Eigen decomposition to suit non-square matrices to reduce multi attribute hand gesture data to feature vectors. SVD optimally exposes the geometric structure of a matrix. In our approach, we replace the basic HMM arithmetic operators by some adequate Type-2 fuzzy operators that permits us to relax the additive constraint of probability measures. Therefore, T2FHMMs are able to handle both random and fuzzy uncertainties existing universally in the sequential data. Experimental results show that T2FHMMs can effectively handle noise and dialect uncertainties in hand signals besides a better classification performance than the classical HMMs. The recognition rate of the proposed system is 100% for uniform hand images and 86.21% for cluttered hand images.

Keywords: hand gesture recognition, hand detection, type-2 fuzzy logic, hidden Markov Model

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Authors: Maria L. Swanson

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Language is a system which constantly changes and reflects social and cultural transformations of a speech community. If it is phonetic system, morphological patterns and syntactic arrangements undergo little charge and are not easily transferable from one language to another, the lexicon has a high degree of flexibility. Borrowings in Arabic have always been an interesting and important subject of study to various fields of linguistics, history and culturology, and there is quite number of works devoted to this subject (al-Khalīl, Sībawīḥ, Jeffery, Belkin, al-Maghribii, Holes, Stetkevich, el-Mawlūdī, between many others). At the same time, the history of borrowing has never been described as a process starting from its originating and up to the present time. Most of the researches study lexical and morphological adaptation of borrowed words for specific or several historical periods or delineate this process on the whole. Meanwhile, we have described the whole history of borrowings in Arabic with the brief depicting of lexical and morphological specifics for each historical period using quantitative method through dividing Arabic borrowings into several groups, basing on the specific of their adaptation of new vocabulary which is tightly related to the global transformations in the Arabic history. We explain reasons for borrowings of specific lexical layers for each historical period together with the description of its morphological specifics. We also use qualitative approach through performing statistics about the share of loan vocabulary in Arabic during different periods and the percentage of borrowings from donor languages. The history of a character and amount of borrowings is a good resource for theoretical and practical lexicography and morphology studies. It is also beneficial for researchers in the field of global and specific national, political and social developments, and different types of contacts.

Keywords: anthropological linguistics, borrowings, historical linguistics, sociolinguistics

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Authors: Marcus Maia

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The present study reports and discusses the use of eye tracking qualitative data in reading workshops in Brazilian middle and high schools and in Generative Syntax and Sentence Processing courses at the undergraduate and graduate levels at the Federal University of Rio de Janeiro, respectively. Both endeavors take the sentential level as the proper object to be metacognitively explored in language education (cf. Chomsky, Gallego & Ott, 2019) to develop innate science forming capacity and knowledge of language. In both projects, non-discrepant qualitative eye tracking data collected and quantitatively analyzed in experimental syntax and psycholinguistic studies carried out in Lapex (Experimental Psycholinguistics Laboratory of the Federal University of Rio de Janeiro) were displayed to students as a point of departure, triggering discussions. Classes would generally start with the display of videos showing eye tracking data, such as gaze plots and heatmaps from several studies in Psycholinguistics and Experimental Syntax that we had already developed in our laboratory. The videos usually triggered discussions with students about linguistic and psycholinguistic issues, such as the reading of sentences for gist, garden-path sentences, syntactic and semantic anomalies, the filled-gap effect, island effects, direct and indirect cause, and recursive constructions, among other topics. Active, problem-solving based methodologies were employed with the objective of stimulating student participation. The communication also discusses the importance of developing full literacy, epistemic vigilance and intellectual self-defense in an infodemic world in the lines of Maia (2022).

Keywords: reading, educational psycholinguistics, eye-tracking, active methodology

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Authors: Lin Dong, Fei Shi

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Based on the railway network and the principles of space syntax, the study attempts to reconstruct the spatial relationship of the passenger network connections from space and time perspective. According to the travel time data of main stations in the Yangtze River Delta urban agglomeration obtained by the Internet, the topological drawing of railway network under different time sections is constructed. With the comprehensive index composed of connection and integration, the accessibility and network operation efficiency of the railway network in different time periods is calculated, while the fairness of the network is analyzed by the fairness indicators constructed with the integration and location entropy from the perspective of horizontal and vertical fairness respectively. From the analysis of the efficiency and fairness of the railway passenger transport network, the study finds: (1) There is a strong regularity in regional system accessibility change; (2) The problems of efficiency and fairness are different in different time periods; (3) The improvement of efficiency will lead to the decline of horizontal fairness to a certain extent, while from the perspective of vertical fairness, the supply-demand situation has changed smoothly with time; (4) The network connection efficiency of Shanghai, Jiangsu and Zhejiang regions is higher than that of the western regions such as Anqing and Chizhou; (5) The marginalization of Nantong, Yancheng, Yangzhou, Taizhou is obvious. The study explores the application of spatial syntactic theory in regional traffic analysis, in order to provide a reference for the development of urban agglomeration transportation network.

Keywords: spatial syntax, the Yangtze River Delta, railway passenger time, efficiency and fairness

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Authors: Marie Komorna, Katerina Hadkova

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One reason why hearing disabilities as compared to other disabilities are considered to be less serious, is the belief that deaf and hard of hearing persons can read and write without problems and can therefore fairly easily compensate for problems related to their limited ability to hear sound. However in reality this is not the case, especially as regards written Czech, deaf persons are often not able to communicate their message clearly to its recipients. Their inability to communicate fully in written language is one of the most severe problems facing a number of deaf persons, a problem which they face and which makes it difficult for them to function in a sound-based environment. Despite this fact, this issue is one which has been given only a minimum of attention in the Czech Republic. That is why we decided to focus our research on this issue, specifically targeting written communication of deaf pupils in primary and secondary schools. The paper summarizes the background and objectives of this research. The written work of deaf respondents was obtained in response to a narrative based on a series of images which depicted a continuous storyline. Based on an analysis of the obtained written work we tried to describe the specifics of the narrative abilities of the deaf authors of these texts. We also analyzed other aspects and specific traits of text written by deaf authors at a phonetic-phonological, lexical-semantic, morphological and syntactic, respectively pragmatic level. Based on the results of the project it will be possible to increase knowledge of the communication abilities of deaf persons in written Czech. The obtained data may be used during future research and for teaching purposes and/or education concepts for teaching Czech to deaf pupils.

Keywords: communication competence, deaf, narrative, written texts

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Authors: Shivani Tiwari, Prathibha Karanth, B. Rajashekhar

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Impairments of syntactic morphology are often considered central in children with Specific Language Impairment (SLI). In English and related languages, deficits of tense-related grammatical morphology could serve as a clinical marker of SLI. Yet, cross-linguistic studies on SLI in the recent past suggest that the nature and severity of morphosyntactic deficits in children with SLI varies with the language being investigated. Therefore, in the present study we investigated the morphosyntactic deficits in a group of children with SLI who speak Kannada, a morphologically complex Dravidian language spoken in Indian subcontinent. A group of 15 children with SLI participated in this study. Two more groups of typical developing children (15 each) matched for language and age to children with SLI, were included as control participants. All participants were assessed for morphosyntactic comprehension and expression using standardized language test and a spontaneous speech task. Results of the study showed that children with SLI differed significantly from age-matched but not language-matched control group, on tasks of both comprehension and expression of morphosyntax. This finding is, however, in contrast with the reports of English-speaking children with SLI who are reported to be poorer than younger MLU-matched children on tasks of morphosyntax. The observed difference in impairments of morphosyntax in Kannada-speaking children with SLI from English-speaking children with SLI is explained based on the morphological richness theory. The theory predicts that children with SLI perform relatively better in morphologically rich language due to occurrence of their frequent and consistent features that mark the morphological markers. The authors, therefore, conclude that language-specific features do influence manifestation of the disorder in children with SLI.

Keywords: specific language impairment, morphosyntax, Kannada, manifestation

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Authors: Raquel Mateo Mendaza, Carmen Novo Urraca

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The current paper presents the elaboration of a corpus database that aligns two different corpora in order to simplify the search of information both for researchers and students of Old English. This database comprises the information contained in two main reference corpora, namely the Dictionary of Old English Corpus (DOEC), compiled at the University of Toronto, and the York-Toronto-Helsinki Parsed Corpus of Old English (YCOE). The first one provides information on all surviving texts written in the Old English language. The latter offers the syntactical and morphological annotation of several texts included in the DOEC. Although both corpora are closely related, as the YCOE includes the DOE source text identifier, the main problem detected is that there is not an alignment of texts that allows for the search of whole fragments to be further analysed in terms of morphology and syntax. The database proposed in this paper gathers all this information and presents it in a simple, more accessible, visual, and educational way. The alignment of fragments has been done in an automatized way. However, some problems have emerged during the creating process particularly related to the lack of correspondence in the division of fragments. For this reason, it has been necessary to revise the whole entries manually to obtain a truthful high-quality product and to carefully indicate the gaps encountered in these corpora. All in all, this database contains more than 60,000 entries corresponding with the DOE fragments annotated by the YCOE. The main strength of the resulting product is its research and teaching implications in the study of Old English. The use of this database will help researchers and students in the study of different aspects of the language, such as inflectional morphology, syntactic behaviour of given words, or translation studies, among others. By means of the search of words or fragments, the annotated information on morphology and syntax will be automatically displayed, automatizing, and speeding up the search of data.

Keywords: alignment, corpus database, morphosyntactic analysis, Old English

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Authors: Emmanuel Nikiema

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This paper examines article incorporation in Mauritian Creole, a French Lexifier Creole which exhibits three forms of article incorporation as illustrated in (1-3). While various analyses of article incorporation have been proposed in the literature, fewer studies have explored the motivation of this widespread phenomenon in Mauritian Creole (MC) as opposed to other French Lexifier Creoles spoken in the Caribbean. For example, Mauritian Creole exhibits 4 times more CV incorporation than Haitian Creole, and 40 times more than Reunion Creole. (1) Consonantal type (C): loraz ‘thunder storm’, lete ‘summer’, zwazo ‘bird’, nide ‘idea’. (2) Syllabic type (CV): lapo ‘skin’, liku ‘neck’, ledo ‘back’, leker ‘heart’, diber ‘butter’. (3) Bi-consonantal (CVC): delo ‘water’, dizef ‘egg’, lizye ‘eye’, dilwil ‘oil’. The goal of this study is twofold: 1) uncover the rules governing the three types of article incorporation in MC, and 2) account for its remarkable occurrence in MC as opposed to its quasi-absence in Reunion Creole. We have collected a corpus of over 700 cases and organized it into three categories (C; CV and CVC). For example, there are 471 examples of CV incorporation in MC against 112 in Haitian Creole and only 12 in Reunion Creole. Two questions can be raised: 1) what is the motivation and distribution of the three types of incorporation in MC, and 2) how can one account for the high volume of incorporation in MC as opposed to its quasi-absence in Reunion Creole? We suggest that article incorporation in MC is related to the structure of nouns in Bantou languages. While previous authors have largely used population settlement data in the colonies during the Creole formation period to justify their analyses, we propose an account based on the syntactic structure of Bantou nouns. This analysis will shed light on the contribution of African languages to the formation of MC, and on to why MC has exhibited more article incorporation cases than any other French Lexifier Creole.

Keywords: article incorporation, creole languages, description, phonology

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Authors: Yi Gu

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The Three-Body Problem by Cixin Liu has been a bestseller Chinese Sci-Fi novel for years since 2008. The book was translated into English by Ken Liu in 2014 and won the prestigious 2015 science fiction and fantasy writing Hugo Award, drawing greater attention from wider international communities. The story exposes the horrors of the Chinese Cultural Revolution in the 1960s, in an intriguing narrative for readers at home and abroad. However, without the access to the source text, western readers may not be aware that the original Chinese version of the book is rich in gender-bias. Some Chinese scholars have applied feminist translation theories to their analysis on this book before, based on isolated selected, cherry-picking examples. Thus this paper aims to obtain a more thorough picture of how translators can cope with gender discrimination and reshape the gendered discourse from the source text, by systematically investigating the lexical and syntactic patterns in the translation of Liu’s entire book of 400 pages. The source text and the translation were downloaded into digital files, automatically aligned at paragraph level and then manually post-edited. They were then compiled into a parallel corpus of 114,629 English words and 204,145 Chinese characters using Sketch Engine. Gender-discrimination markers such as the overuse of ‘girl’ to describe an adult woman were searched in the source text, and the alignment made it possible to identify the strategies adopted by the translator to mitigate gender discrimination. The results provide a framework for translators to address gender bias. The study also shows how corpus methods can be used to further research in feminist translation and critical discourse analysis.

Keywords: corpus, discourse analysis, feminist translation, science fiction translation

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Authors: Ali Algryani

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Ellipsis involves the omission of an item or items that can be recovered from the preceding clause. Ellipsis is used as a cohesion marker; it enhances the cohesiveness of a text/discourse as a clause is interpretable only through making reference to an antecedent clause. The present study attempts to investigate the linguistic phenomenon of ellipsis from a translation perspective. It is mainly concerned with how ellipsis is translated from English into Arabic. The study covers different forms of ellipsis, such as noun phrase ellipsis, verb phrase ellipsis, gapping, pseudo-gapping, stripping, and sluicing. The primary aim of the study, apart from discussing the use and function of ellipsis, is to find out how such ellipsis phenomena are dealt with in English-Arabic translation and determine the implications of the translations of elliptical structures into Arabic. The study is based on the analysis of Dhofar University (DU) students' translations of sentences containing different forms of ellipsis. The initial findings of the study indicate that due to differences in syntactic structures and stylistic preferences between English and Arabic, Arabic tends to use lexical repetition in the translation of some elliptical structures, thus achieving a higher level of explicitness. This implies that Arabic tends to prefer lexical repetition to create cohesion more than English does. Furthermore, the study also reveals that the improper translation of ellipsis leads to interpretations different from those understood from the source text. Such mistranslations can be attributed to student translators’ lack of awareness of the use and function of ellipsis as well as the stylistic preferences of both languages. This has pedagogical implications on the teaching and training of translation students at DU. Students' linguistic competence needs to be enhanced through teaching linguistics-related issues with reference to translation and both languages, .i.e. source and target languages and with special emphasis on their use, function and stylistic preferences.

Keywords: cohesion, ellipsis, explicitness, lexical repetition

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Authors: Irene Yi

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Machine learning, natural language processing, and neural network models of language are becoming more and more prevalent in the fields of technology and linguistics today. Training data for machines are at best, large corpora of human literature and at worst, a reflection of the ugliness in society. Machines have been trained on millions of human books, only to find that in the course of human history, derogatory and sexist adjectives are used significantly more frequently when describing females in history and literature than when describing males. This is extremely problematic, both as training data, and as the outcome of natural language processing. As machines start to handle more responsibilities, it is crucial to ensure that they do not take with them historical sexist and misogynistic notions. This paper gathers data and algorithms from neural network models of language having to deal with syntax, semantics, sociolinguistics, and text classification. Results are significant in showing the existing intentional and unintentional misogynistic notions used to train machines, as well as in developing better technologies that take into account the semantics and syntax of text to be more mindful and reflect gender equality. Further, this paper deals with the idea of non-binary gender pronouns and how machines can process these pronouns correctly, given its semantic and syntactic context. This paper also delves into the implications of gendered grammar and its effect, cross-linguistically, on natural language processing. Languages such as French or Spanish not only have rigid gendered grammar rules, but also historically patriarchal societies. The progression of society comes hand in hand with not only its language, but how machines process those natural languages. These ideas are all extremely vital to the development of natural language models in technology, and they must be taken into account immediately.

Keywords: gendered grammar, misogynistic language, natural language processing, neural networks

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Authors: Burak Oksuzoglu, Savas Yildirim, Ferhat Kutlu

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Opinion mining (OM) is one of the natural language processing (NLP) problems to determine the polarity of opinions, mostly represented on a positive-neutral-negative axis. The data for OM is usually collected from various social media platforms. In an era where social media has considerable control over companies’ futures, it’s worth understanding social media and taking actions accordingly. OM comes to the fore here as the scale of the discussion about companies increases, and it becomes unfeasible to gauge opinion on individual levels. Thus, the companies opt to automize this process by applying machine learning (ML) approaches to their data. For the last two decades, OM or sentiment analysis (SA) has been mainly performed by applying ML classification algorithms such as support vector machines (SVM) and Naïve Bayes to a bag of n-gram representations of textual data. With the advent of deep learning and its apparent success in NLP, traditional methods have become obsolete. Transfer learning paradigm that has been commonly used in computer vision (CV) problems started to shape NLP approaches and language models (LM) lately. This gave a sudden rise to the usage of the pretrained language model (PTM), which contains language representations that are obtained by training it on the large datasets using self-supervised learning objectives. The PTMs are further fine-tuned by a specialized downstream task dataset to produce efficient models for various NLP tasks such as OM, NER (Named-Entity Recognition), Question Answering (QA), and so forth. In this study, the traditional and modern NLP approaches have been evaluated for OM by using a sizable corpus belonging to a large private company containing about 76,000 comments in Turkish: SVM with a bag of n-grams, and two chosen pre-trained models, multilingual universal sentence encoder (MUSE) and bidirectional encoder representations from transformers (BERT). The MUSE model is a multilingual model that supports 16 languages, including Turkish, and it is based on convolutional neural networks. The BERT is a monolingual model in our case and transformers-based neural networks. It uses a masked language model and next sentence prediction tasks that allow the bidirectional training of the transformers. During the training phase of the architecture, pre-processing operations such as morphological parsing, stemming, and spelling correction was not used since the experiments showed that their contribution to the model performance was found insignificant even though Turkish is a highly agglutinative and inflective language. The results show that usage of deep learning methods with pre-trained models and fine-tuning achieve about 11% improvement over SVM for OM. The BERT model achieved around 94% prediction accuracy while the MUSE model achieved around 88% and SVM did around 83%. The MUSE multilingual model shows better results than SVM, but it still performs worse than the monolingual BERT model.

Keywords: BERT, MUSE, opinion mining, pretrained language model, SVM, Turkish

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Authors: Nancy Retzlaff, Sarah J. Berkemer, Trudie Strauss

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In the last couple of decades, the advent of digitalization of any kind of data was probably one of the major advances in all fields of study. This paves the way for also analysing these data even though they might come from disciplines where there was no initial computational necessity to do so. Especially in linguistics, one can find a rather manual tradition. Still when considering studies that involve the history of language families it is hard to overlook the striking similarities to bioinformatics (phylogenetic) approaches. Alignments of words are such a fairly well studied example of an application of bioinformatics methods to historical linguistics. In this paper we will not only consider alignments of strings, i.e., words in this case, but also alignments of syntax trees of selected Indo-European languages. Based on initial, crude alignments, a sophisticated scoring model is trained on both letters and syntactic features. The aim is to gain a better understanding on which features in two languages are related, i.e., most likely to have the same root. Initially, all words in two languages are pre-aligned with a basic scoring model that primarily selects consonants and adjusts them before fitting in the vowels. Mixture models are subsequently used to filter ‘good’ alignments depending on the alignment length and the number of inserted gaps. Using these selected word alignments it is possible to perform tree alignments of the given syntax trees and consequently find sentences that correspond rather well to each other across languages. The syntax alignments are then filtered for meaningful scores—’good’ scores contain evolutionary information and are therefore used to train the sophisticated scoring model. Further iterations of alignments and training steps are performed until the scoring model saturates, i.e., barely changes anymore. A better evaluation of the trained scoring model and its function in containing evolutionary meaningful information will be given. An assessment of sentence alignment compared to possible phrase structure will also be provided. The method described here may have its flaws because of limited prior information. This, however, may offer a good starting point to study languages where only little prior knowledge is available and a detailed, unbiased study is needed.

Keywords: alignments, bioinformatics, comparative linguistics, historical linguistics, statistical methods

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Authors: Yashaswini Channabasavegowda, Hema Nagaraj

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Aim: The current study aims at discovering word-class deficits concerning the noun-verb ratio in confrontation naming, picture description, and picture-word matching tasks. A total of ten persons with aphasia (PWA) and ten age-matched neurotypical individuals (NTI) were recruited for the study. The research includes both behavioural and objective measures to assess the word class deficits in PWA. Objective: The main objective of the research is to identify word class deficits seen in persons with aphasia, using various speech eliciting tasks. Method: The study was conducted in the L1 of the participants, considered to be Kannada. Action naming test and Boston naming test adapted to the Kannada version are administered to the participants; also, a picture description task is carried out. Picture-word matching task was carried out using e-prime software (version 2) to measure the accuracy and reaction time with respect to identification verbs and nouns. The stimulus was presented through auditory and visual modes. Data were analysed to identify errors noticed in the naming of nouns versus verbs, with respect to the Boston naming test and action naming test and also usage of nouns and verbs in the picture description task. Reaction time and accuracy for picture-word matching were extracted from the software. Results: PWA showed a significant difference in sentence structure compared to age-matched NTI. Also, PWA showed impairment in syntactic measures in the picture description task, with fewer correct grammatical sentences and fewer correct usage of verbs and nouns, and they produced a greater proportion of nouns compared to verbs. PWA had poorer accuracy and lesser reaction time in the picture-word matching task compared to NTI, and accuracy was higher for nouns compared to verbs in PWA. The deficits were noticed irrespective of the cause leading to aphasia.

Keywords: nouns, verbs, aphasia, naming, description

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Authors: Vishal Raj, Noorhan Abbas

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Ambiguity in NLP (Natural language processing) refers to the ability of a word, phrase, sentence, or text to have multiple meanings. This results in various kinds of ambiguities such as lexical, syntactic, semantic, anaphoric and referential am-biguities. This study is focused mainly on solving the issue of Lexical ambiguity. Word Sense Disambiguation (WSD) is an NLP technique that aims to resolve lexical ambiguity by determining the correct meaning of a word within a given context. Most WSD solutions rely on words for training and testing, but we have used lemma and Part of Speech (POS) tokens of words for training and testing. Lemma adds generality and POS adds properties of word into token. We have designed a novel method to create an affinity matrix to calculate the affinity be-tween any pair of lemma_POS (a token where lemma and POS of word are joined by underscore) of given training set. Additionally, we have devised an al-gorithm to create the sense clusters of tokens using affinity matrix under hierar-chy of POS of lemma. Furthermore, three different mechanisms to predict the sense of target word using the affinity/similarity value are devised. Each contex-tual token contributes to the sense of target word with some value and whichever sense gets higher value becomes the sense of target word. So, contextual tokens play a key role in creating sense clusters and predicting the sense of target word, hence, the model is named Contextual SenSe Model (CSM). CSM exhibits a noteworthy simplicity and explication lucidity in contrast to contemporary deep learning models characterized by intricacy, time-intensive processes, and chal-lenging explication. CSM is trained on SemCor training data and evaluated on SemEval test dataset. The results indicate that despite the naivety of the method, it achieves promising results when compared to the Most Frequent Sense (MFS) model.

Keywords: word sense disambiguation (wsd), contextual sense model (csm), most frequent sense (mfs), part of speech (pos), natural language processing (nlp), oov (out of vocabulary), lemma_pos (a token where lemma and pos of word are joined by underscore), information retrieval (ir), machine translation (mt)

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Authors: Irene Yi

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Machine learning, natural language processing, and neural network models of language are becoming more and more prevalent in the fields of technology and linguistics today. Training data for machines are at best, large corpora of human literature and at worst, a reflection of the ugliness in society. Computational linguistics is a growing field dealing with such issues of data collection for technological development. Machines have been trained on millions of human books, only to find that in the course of human history, derogatory and sexist adjectives are used significantly more frequently when describing females in history and literature than when describing males. This is extremely problematic, both as training data, and as the outcome of natural language processing. As machines start to handle more responsibilities, it is crucial to ensure that they do not take with them historical sexist and misogynistic notions. This paper gathers data and algorithms from neural network models of language having to deal with syntax, semantics, sociolinguistics, and text classification. Computational analysis on such linguistic data is used to find patterns of misogyny. Results are significant in showing the existing intentional and unintentional misogynistic notions used to train machines, as well as in developing better technologies that take into account the semantics and syntax of text to be more mindful and reflect gender equality. Further, this paper deals with the idea of non-binary gender pronouns and how machines can process these pronouns correctly, given its semantic and syntactic context. This paper also delves into the implications of gendered grammar and its effect, cross-linguistically, on natural language processing. Languages such as French or Spanish not only have rigid gendered grammar rules, but also historically patriarchal societies. The progression of society comes hand in hand with not only its language, but how machines process those natural languages. These ideas are all extremely vital to the development of natural language models in technology, and they must be taken into account immediately.

Keywords: computational analysis, gendered grammar, misogynistic language, neural networks

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Authors: Zelalem Fantahun

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Part-of-speech tagging is the process of assigning a part-of-speech or other lexical class marker to each word into naturally occurring text. Part-of-speech tagging is the most fundamental and basic task almost in all natural language processing. In natural language processing, the problem of providing large amount of manually annotated data is a knowledge acquisition bottleneck. Since, Amharic is one of under-resourced language, the availability of tagged corpus is the bottleneck problem for natural language processing especially for POS tagging. A promising direction to tackle this problem is to provide a system that does not require manually tagged data. In unsupervised learning, the learner is not provided with classifications. Unsupervised algorithms seek out similarity between pieces of data in order to determine whether they can be characterized as forming a group. This paper explicates the development of unsupervised part-of-speech tagger using K-Means clustering for Amharic language since large amount of data is produced in day-to-day activities. In the development of the tagger, the following procedures are followed. First, the unlabeled data (raw text) is divided into 10 folds and tokenization phase takes place; at this level, the raw text is chunked at sentence level and then into words. The second phase is feature extraction which includes word frequency, syntactic and morphological features of a word. The third phase is clustering. Among different clustering algorithms, K-means is selected and implemented in this study that brings group of similar words together. The fourth phase is mapping, which deals with looking at each cluster carefully and the most common tag is assigned to a group. This study finds out two features that are capable of distinguishing one part-of-speech from others these are morphological feature and positional information and show that it is possible to use unsupervised learning for Amharic POS tagging. In order to increase performance of the unsupervised part-of-speech tagger, there is a need to incorporate other features that are not included in this study, such as semantic related information. Finally, based on experimental result, the performance of the system achieves a maximum of 81% accuracy.

Keywords: POS tagging, Amharic, unsupervised learning, k-means

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Authors: Zhao Gao, Eran Edirisinghe

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The production of an accurate sketch of a suspect based on a verbal description obtained from a witness is an essential task for most criminal investigations. The criminal investigation system employs specifically trained professional artists to manually draw a facial image of the suspect according to the descriptions of an eyewitness for subsequent identification. Within the advancement of Deep Learning, Recurrent Neural Networks (RNN) have shown great promise in Natural Language Processing (NLP) tasks. Additionally, Generative Adversarial Networks (GAN) have also proven to be very effective in image generation. In this study, a trained GAN conditioned on textual features such as keywords automatically encoded from a verbal description of a human face using an RNN is used to generate photo-realistic facial images for criminal investigations. The intention of the proposed system is to map corresponding features into text generated from verbal descriptions. With this, it becomes possible to generate many reasonably accurate alternatives to which the witness can use to hopefully identify a suspect from. This reduces subjectivity in decision making both by the eyewitness and the artist while giving an opportunity for the witness to evaluate and reconsider decisions. Furthermore, the proposed approach benefits law enforcement agencies by reducing the time taken to physically draw each potential sketch, thus increasing response times and mitigating potentially malicious human intervention. With publically available 'CelebFaces Attributes Dataset' (CelebA) and additionally providing verbal description as training data, the proposed architecture is able to effectively produce facial structures from given text. Word Embeddings are learnt by applying the RNN architecture in order to perform semantic parsing, the output of which is fed into the GAN for synthesizing photo-realistic images. Rather than the grid search method, a metaheuristic search based on genetic algorithms is applied to evolve the network with the intent of achieving optimal hyperparameters in a fraction the time of a typical brute force approach. With the exception of the ‘CelebA’ training database, further novel test cases are supplied to the network for evaluation. Witness reports detailing criminals from Interpol or other law enforcement agencies are sampled on the network. Using the descriptions provided, samples are generated and compared with the ground truth images of a criminal in order to calculate the similarities. Two factors are used for performance evaluation: The Structural Similarity Index (SSIM) and the Peak Signal-to-Noise Ratio (PSNR). A high percentile output from this performance matrix should attribute to demonstrating the accuracy, in hope of proving that the proposed approach can be an effective tool for law enforcement agencies. The proposed approach to criminal facial image generation has potential to increase the ratio of criminal cases that can be ultimately resolved using eyewitness information gathering.

Keywords: RNN, GAN, NLP, facial composition, criminal investigation

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Authors: Amir Reza Asnafi, Masoumeh Kazemizadeh, Najmeh Salemi

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Due to the diversity of information resources in the web0.2 environment, which is increasing in number from time to time, the social tagging system should be used to discuss Internet resources. Studying the relevance of social tags to thematic headings can help enrich resources and make them more accessible to resources. The present research is of applied-theoretical type and research method of content analysis. In this study, using the listing method and content analysis, the level of accurate, approximate, relative, and non-conformity of social labels of books available in the field of information science and bibliography of Kitabrah website with Persian subject headings was determined. The exact matching of subject headings with social tags averaged 22 items, the approximate matching of subject headings with social tags averaged 36 items, the relative matching of thematic headings with social tags averaged 36 social items, and the average matching titles did not match the title. The average is 116. According to the findings, the exact matching of subject headings with social labels is the lowest and the most inconsistent. This study showed that the average non-compliance of subject headings with social labels is even higher than the sum of the three types of exact, relative, and approximate matching. As a result, the relevance of thematic titles to social labels is low. Due to the fact that the subject headings are in the form of static text and users are not allowed to interact and insert new selected words and topics, and on the other hand, in websites based on Web 2 and based on the social classification system, this possibility is available for users. An important point of the present study and the studies that have matched the syntactic and semantic matching of social labels with thematic headings is that the degree of conformity of thematic headings with social labels is low. Therefore, these two methods can complement each other and create a hybrid cataloging that includes subject headings and social tags. The low level of conformity of thematic headings with social tags confirms the results of backgrounds and writings that have compared the social tags of books with the thematic headings of the Library of Congress. It is not enough to match social labels with thematic headings. It can be said that these two methods can be complementary.

Keywords: Web 2/0, social tags, subject headings, hybrid cataloging

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Authors: Svetlana Strinyuk, Viacheslav Lanin

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Academic English has become lingua franca for international scientific community which stimulates universities to introduce English for Specific Purposes (EAP) courses into curriculum. Teaching L2 EAP students might be fulfilled with corpus technologies and digital stylistics. A special software developed to reach the manifold task of teaching, assessing and researching academic writing of L2 students on basis of digital stylistics and multidimensional analysis was created. A set of annotations (style markers) – grammar, lexical and syntactic features most significant of academic writing was built. Contrastive comparison of two corpora “model corpus”, subject domain limited papers published by competent writers in leading academic journals, and “students’ corpus”, subject domain limited papers written by last year students allows to receive data about the features of academic writing underused or overused by L2 EAP student. Both corpora are tagged with a special software created in GATE Developer. Style markers within the framework of research might be replaced depending on the relevance and validity of the result which is achieved from research corpora. Thus, selecting relevant (high frequency) style markers and excluding less relevant, i.e. less frequent annotations, high validity of the model is achieved. Software allows to compare the data received from processing model corpus to students’ corpus and get reports which can be used in teaching and assessment. The less deviation from the model corpus students demonstrates in their writing the higher is academic writing skill acquisition. The research showed that several style markers (hedging devices) were underused by L2 EAP students whereas lexical linking devices were used excessively. A special software implemented into teaching of EAP courses serves as a successful visual aid, makes assessment more valid; it is indicative of the degree of writing skill acquisition, and provides data for further research.

Keywords: corpus technologies in EAP teaching, multidimensional analysis, GATE Developer, corpus stylistics

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Authors: Varvara Tyurina

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In the age of globalization Internet communication as a new format of interactions have become an integral part of our daily routine. Internet environment allows for new conditions and provides participants to a communication act with extra communication tools which can be used on Internet forums or in chat rooms. As a result communicants tend to alternate their behavior patterns in contrast to those practiced in live communication. It is not yet clear which communication strategies participants to Internet communication abide by and what determines their choices. Given the continually changing environment of a forum or a chat the behavior of a communicant can be interpreted in terms of autopoiesis theory which sees adaptation as the major tool for coexistence between the living system and its niche. Each communication act is seen as interaction between the communicant (i.e. the living system) and the overall environment of the forum (i.e. the niche) rather than one particular interlocutor. When communicating via the Internet participants are believed to aim at reaching a balance between themselves and the environment of a forum or a chat. The research focuses on unveiling the adaptation strategies employed by a communicant in particular cases and looks into the reasons they are employed. There is a correlation between language faculty of the communicants and the strategies they opt for when communicating on Internet forums and in chat rooms. The research included an experiment with a sample of Russian-English asymmetric bilinguals aged 16-25. Respondents were given two texts of equivalent contents, but of different language complexity. They had to respond to the texts as if they were making a reciprocal comment at a forum. It has been revealed that when communicants realize that their language faculty is not sufficient to understand the initial text they tend to amend their communication strategy in order to maintain the balance with the niche (remain involved in the communication). Most common strategies for responding to a difficult-to-understand text were self-presentation, veiling poor language faculty and response evasion. The research has so far focused on a very narrow aspect of correlation between language faculty and communication behavior, namely the syntactic and lexicological complexity of initial texts. It is essential to conduct a series of experiments that dwell on other characteristics of the texts to determine the range of cases when language faculty determines the choice of adaptation strategy.

Keywords: adaptation, communication strategies, internet communication, verbal interaction, autopoiesis theory

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Authors: Lexi Li, Vanessa H. K. Pang

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This study aims to demonstrate how native and learner corpora can be used to enhance modal verb treatment in EFL textbooks in mainland China. It contributes to a corpus-informed and learner-centered design of grammar presentation in EFL textbooks that enhances the authenticity and appropriateness of textbook language for target learners. The linguistic focus is will, would, can, could, may, might, shall, should, must. The native corpus is the spoken component of BNC2014 (hereafter BNCS2014). The spoken part is chosen because pedagogical purpose of the textbooks is communication-oriented. Using the standard query option of CQPweb, 5% of each of the nine modals was sampled from BNCS2014. The learner corpus is the POS-tagged Ten-thousand English Compositions of Chinese Learners (TECCL). All the essays under the 'secondary school' section were selected. A series of five secondary coursebooks comprise the textbook corpus. All the data in both the learner and the textbook corpora are retrieved through the concordance functions of WordSmith Tools (version, 5.0). Data analysis was divided into two parts. The first part compared the patterns of modal verbs in the textbook corpus and BNC2014 with respect to distributional features, semantic functions, and co-occurring constructions to examine whether the textbooks reflect the authentic use of English. Secondly, the learner corpus was analyzed in terms of the use (distributional features, semantic functions, and co-occurring constructions) and the misuse (syntactic errors, e.g., she can sings*.) of the nine modal verbs to uncover potential difficulties that confront learners. The analysis of distribution indicates several discrepancies between the textbook corpus and BNCS2014. The first four most frequent modal verbs in BNCS2014 are can, would, will, could, while can, will, should, could are the top four in the textbooks. Most strikingly, there is an unusually high proportion of can (41.1%) in the textbooks. The results on different meanings shows that will, would and must are the most problematic. For example, for will, the textbooks contain 20% more occurrences of 'volition' and 20% less of 'prediction' than those in BNCS2014. Regarding co-occurring structures, the textbooks over-represented the structure 'modal +do' across the nine modal verbs. Another major finding is that the structure of 'modal +have done' that frequently co-occur with could, would, should, and must is underused in textbooks. Besides, these four modal verbs are the most difficult for learners, as the error analysis shows. This study demonstrates how the synergy of native and learner corpora can be harnessed to improve EFL textbook presentation of modal verbs in a way that textbooks can provide not only authentic language used in natural discourse but also appropriate design tailed for the needs of target learners.

Keywords: English as Foreign Language, EFL textbooks, learner corpus, modal verbs, native corpus

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Authors: Wujian Han

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In the process of human interaction and communication, speech act verbs are considered to be the most active component and the main means for information transmission, and are also taken as an indication of the structure of linguistic behavior. The theoretical value and practical significance of such everyday built-in metalanguage have long been recognized. This paper, which is part of a bigger study, is aimed to provide useful insights for a more precise and systematic application to speech act verbs translation between English and Chinese, especially with regard to the degree to which generic integrity is maintained in the practice of translation of legal documents. In this study, the corpus, i.e. Chinese legal texts and their English translations, English legal texts, ordinary Chinese texts, and ordinary English texts, serve as a testing ground for examining contrastively the usage of English and Chinese directive speech act verbs in legal genre. The scope of this paper is relatively wide and essentially covers all directive speech act verbs which are used in ordinary English and Chinese, such as order, command, request, prohibit, threat, advice, warn and permit. The researcher, by combining the corpus methodology with a contrastive perspective, explored a range of characteristics of English and Chinese directive speech act verbs including their semantic, syntactic and pragmatic features, and then contrasted them in a structured way. It has been found that there are similarities between English and Chinese directive speech act verbs in legal genre, such as similar semantic components between English speech act verbs and their translation equivalents in Chinese, formal and accurate usage of English and Chinese directive speech act verbs in legal contexts. But notable differences have been identified in areas of difference between their usage in the original Chinese and English legal texts such as valency patterns and frequency of occurrences. For example, the subjects of some directive speech act verbs are very frequently omitted in Chinese legal texts, but this is not the case in English legal texts. One of the practicable methods to achieve adequacy and conciseness in speech act verb translation from Chinese into English in legal genre is to repeat the subjects or the message with discrepancy, and vice versa. In addition, translation effects such as overuse and underuse of certain directive speech act verbs are also found in the translated English texts compared to the original English texts. Legal texts constitute a particularly valuable material for speech act verb study. Building up such a contrastive picture of the Chinese and English speech act verbs in legal language would yield results of value and interest to legal translators and students of language for legal purposes and have practical application to legal translation between English and Chinese.

Keywords: contrastive analysis, corpus-based, directive speech act verbs, legal texts, translation between English and Chinese

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Authors: Mariam Matiashvili

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Argumentation is an integral part of our daily communications - formal or informal. Argumentative reasoning, techniques, and language tools are used both in personal conversations and in the business environment. Verbalization of the opinions requires the use of extraordinary syntactic-pragmatic structural quantities - arguments that add credibility to the statement. The study of argumentative structures allows us to identify the linguistic features that make the text argumentative. Knowing what elements make up an argumentative text in a particular language helps the users of that language improve their skills. Also, natural language processing (NLP) has become especially relevant recently. In this context, one of the main emphases is on the computational processing of argumentative texts, which will enable the automatic recognition and analysis of large volumes of textual data. The research deals with the linguistic analysis of the argumentative structures of Georgian political speeches - particularly the linguistic structure, characteristics, and functions of the parts of the argumentative text - claims, support, and attack statements. The research aims to describe the linguistic cues that give the sentence a judgmental/controversial character and helps to identify reasoning parts of the argumentative text. The empirical data comes from the Georgian Political Corpus, particularly TV debates. Consequently, the texts are of a dialogical nature, representing a discussion between two or more people (most often between a journalist and a politician). The research uses the following approaches to identify and analyze the argumentative structures Lexical Classification & Analysis - Identify lexical items that are relevant in argumentative texts creating process - Creating the lexicon of argumentation (presents groups of words gathered from a semantic point of view); Grammatical Analysis and Classification - means grammatical analysis of the words and phrases identified based on the arguing lexicon. Argumentation Schemas - Describe and identify the Argumentation Schemes that are most likely used in Georgian Political Speeches. As a final step, we analyzed the relations between the above mentioned components. For example, If an identified argument scheme is “Argument from Analogy”, identified lexical items semantically express analogy too, and they are most likely adverbs in Georgian. As a result, we created the lexicon with the words that play a significant role in creating Georgian argumentative structures. Linguistic analysis has shown that verbs play a crucial role in creating argumentative structures.

Keywords: georgian, argumentation schemas, argumentation structures, argumentation lexicon

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Authors: Mehdi Damaliamiri

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Undoubtedly, the power of language is hardly a new topic; indeed, the persuasive power of language accompanied by ideology has long been recognized in different aspects of life. The two and a half thousand-year-old Bisitun inscriptions in Iran, proclaiming the victories of the Persian King, Darius, are considered by some historians to have been an early example of the use of propaganda. Added to this, the modern age is the true cradle of fully-fledged ideologies and the ongoing process of centrifugal ideologization. The most visible work on ideology today within the field of linguistics is “Critical Discourse Analysis” (CDA). The focus of CDA is on “uncovering injustice, inequality, taking sides with the powerless and suppressed” and making “mechanisms of manipulation, discrimination, demagogy, and propaganda explicit and transparent.” possible way of relating language to ideology is to propose that ideology and language are inextricably intertwined. From this perspective, language is always ideological, and ideology depends on the language. All language use involves ideology, and so ideology is ubiquitous – in our everyday encounters, as much as in the business of the struggle for power within and between the nation-states and social statuses. At the same time, ideology requires language. Its key characteristics – its power and pervasiveness, its mechanisms for continuity and for change – all come out of the inner organization of language. The two phenomena are homologous: they share the same evolutionary trajectory. To get a more robust portrait of the power and ideology, we need to examine its potential place in the structure, and consider how such structures pattern in terms of the functional elements which organize meanings in the clause. This is based on the belief that all grammatical, including syntactic, knowledge is stored mentally as constructions have become immensely popular. When the structure of the clause is taken into account, the power and ideology have a preference for Complement over Subject and Adjunct. The subject is a central interpersonal element in discourse: it is one of two elements that form the central interactive nub of a proposition. Conceptually, there are countless ways of construing a given event and linguistically, a variety of grammatical devices that are usually available as alternate means of coding a given conception, such as political crime and corruption. In the theory of construal, then, which, like transitivity in Halliday, makes options available, Cognitive Linguistics can offer a cognitive account of ideology in language, where ideology is made possible by the choices a language allows for representing the same material situation in different ways. The possibility of promoting alternative construals of the same reality means that any particular choice in representation is always ideologically constrained or motivated and indicates the perspective and interests of the text-producer.

Keywords: power, ideology, court, discourse

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