Papers reviewed and determined not to be word norm studies. Use the flag icon to report errors or suggest re-inclusion.
18265 papers
Abstract In recent years, the study of codeswitching has made great strides by leveraging a multidisciplinary approach that integrates insights from experimental psycholinguistics, corpus linguistics, cognitive psychology, neurolinguistics, and other allied fields. We provide an overview of 2 main strands of this research, focusing on the control process model of codeswitching (e.g., Green, 2018), the variable equivalence hypothesis (e.g., Torres Cacoullos, 2020), and the ways in which these accounts of codeswitching behavior intersect and complement one another. We argue that the common insight of these 2 distinct approaches is their focus on conventionalized linguistic norms at the level of the speech community. The second portion of the article sheds light on how various aspects of codeswitching experience give rise to adaptive change through bilingual phenotyping, highlighting the centrality of our mentor Judy Kroll's contributions to this research. Finally, we present a social network analysis of Judy's research publications and argue that the high degree of interconnectivity in Judy's research network, combined with the many positive community norms that she has been instrumental in establishing, have greatly benefited both the individual members of the network and the research enterprise itself.
Graphic health warnings (GHWs) are regarded a highly cost-effective public policy to communicate the health risks involved in smoking, mainly when they trigger negative emotional reactions. GHWs promote intentions to quit among smokers and prevent smoking initiation among non-smokers. In three experiments, we study how smokers and nonsmokers differ in implicit and explicit measures of emotional reactions towards GHWs. Experiment 1 used the Self-Assessment Manikin to measure explicit emotional (arousal and valence) ratings for six warnings published in tobacco products. Experiment 2 was similar to Experiment 1 but smokers and nonsmokers rated a new set of 36 GHWs not yet published. Experiment 3 used an implicit task, the Affect Misattribution Procedure, to evaluate and compare the affective responses to GHWs provided by smokers and non-smokers. Experiments 1 and 2 showed that smokers explicitly reported weaker negative emotional reactions to both familiar and unfamiliar GHWs compared to nonsmokers. Experiment 3 showed similar levels of negative implicit emotional responses among smokers and nonsmokers. Our data suggest that the decreased affective response involves high-order cognitive elaboration and evaluations of the messages conveyed by GHW, while early negative emotions triggered by the graphic component of the warnings similarly affect smokers and non-smokers. We propose that implicit measures may serve as additional and inexpensive tools for dissociating explicit biased affective responses of smokers towards GHWs from automatic emotional responses. In particular, the affect misattribution procedure may help to design warnings that communicate the risks of smoking but prevent adverse outcomes such as cognitive dissonance.
Abstract Older adults with depression have a high incidence of sleep disturbance which is posited to be mechanistically involved in maladaptive overnight emotional memory consolidation. In older adults (≥ 50 years) with and without depression, we aimed to compare group differences in overnight emotional memory and rapid eye movement (REM) and non-rapid eye movement (NREM) (N2 and N3) sleep disturbance. Secondly, we investigated the relationship between emotional memory consolidation, self-report emotional valence and arousal perception, and sleep disturbance. Participants underwent overnight PSG with high-density EEG. An emotional memory image task with concurrent subjective emotional arousal and valence rating was completed before and after sleep. REM sleep disturbance was measured by REM sleep duration, global REM gamma and alpha activity and REM EEG arousal index. NREM sleep disturbance was measured by NREM sleep duration, global NREM delta, alpha and sigma power, and NREM EEG arousal index. T-tests and non-parametric tests were used for group comparisons. Linear regressions were used to assess relationships between sleep disturbance and emotional memory. Twenty-two older adults (Depression: n = 12, Control: n = 10) with a mean age of 63.7 ± 6.5 years completed the study. Older adults with depression demonstrated differences in overnight perception of emotional valence and arousal for negative information, suggesting sleep may be involved in emotion perception. Global delta power in NREM was reduced in older adults with depression, suggestive of homeostatic alterations. However, no robust associations between overnight memory consolidation, emotional valence or arousal and REM or NREM sleep disturbance were observed.
Cultural beliefs and practices find expressions through rituals. Birth is a rite of passage and children are perceived as special gift from the Supreme Being. As such, pregnancy and childbirth are special events cherished and celebrated through varied rituals in different cultures worldwide. Thus, pregnancy and childbirth are not only biological events, but also socially and culturally constructed with associated symbols that represent the social identities and cultural values of the Bakossi people of the South West Region of Cameroon who speak Akoosè language and use it during such rituals. Ritual and language are greatly related. This paper aims to explore the embodied language of ritual after child birth in Akoosè and people’s possession of a sacred but rare ability to use language in a peculiar way to orthodox linguistic norms especially while looking at Birth Songs, burying of the placenta, incantations and the language during libation while welcoming the child home. The ritual language used is an essential aspect that reflects the values and customs of the people given the variations in the language used like the use of metaphors, proverbs and other literary devices, giving the ceremony a poetic and symbolic feel. Language which is one of the principal issues in this study is defined by Sone, (2016) as a systematic means which human beings use in the communication of thoughts, ideas, values, norms and feelings. Data realized is through Tape and video recordings and participant observation. It is assumed that the custodians of the spoken discourse, is far more than mere use of words, rather it is a linguistically significant variety when studied within the Akoosè /Akɔ́ɔ́sè/context.
This paper delves into the text processing aspects of Language Computing, which enables computers to understand, interpret, and generate human language. Focusing on tasks such as speech recognition, machine translation, sentiment analysis, text summarization, and language modelling, language computing integrates disciplines including linguistics, computer science, and cognitive psychology to create meaningful human-computer interactions. Recent advancements in deep learning have made computers more accessible and capable of independent learning and adaptation. In examining the landscape of language computing, the paper emphasises foundational work like encoding, where Tamil transitioned from ASCII to Unicode, enhancing digital communication. It discusses the development of computational resources, including raw data, dictionaries, glossaries, annotated data, and computational grammars, necessary for effective language processing. The challenges of linguistic annotation, the creation of treebanks, and the training of large language models are also covered, emphasising the need for high-quality, annotated data and advanced language models. The paper underscores the importance of building practical applications for languages like Tamil to address everyday communication needs, highlighting gaps in current technology. It calls for increased research collaboration, digitization of historical texts, and fostering digital usage to ensure the comprehensive development of Tamil language processing, ultimately enhancing global communication and access to digital services.
Neural network accelerators have become essential in addressing the growing computational demands of AI and machine learning applications. This study evaluates the performance of neural network accelerators implemented on FPGA and ASIC platforms, utilizing TensorFlow for neural network model design and Xilinx Vivado for FPGA hardware prototyping. Benchmark tests were conducted using CNNs, RNNs, and Transformer models on datasets such as CIFAR-10, ImageNet, and Penn Treebank (PTB). Key performance metrics, including latency, power consumption, throughput, and accuracy, were analyzed. Results revealed that ASIC outperformed FPGA across all metrics, with 40% lower latency, 46.7% reduced power consumption, and 33% higher throughput, while maintaining a slightly higher accuracy (94% vs. 92%). The discussion highlighted ASIC's suitability for real-time, power-efficient AI tasks, whereas FPGA remains advantageous for prototyping and adaptable AI architectures. In conclusion, ASIC excels in performance and efficiency, making it ideal for deployment in resource-constrained AI applications, while FPGA serves as a flexible platform for iterative design and experimentation. These findings provide valuable insights for selecting hardware platforms based on application-specific requirements in neural network microcircuit design.
Forensic linguistics, a multidisciplinary field that applies linguistic analysis to legal and professional contexts, plays a critical role in legal proceedings and investigations. This study explores its applications in Uzbekistan, where the intersection of linguistics and law is particularly significant due to the country's linguistic diversity and socio-cultural dynamics. The article examines cases involving insults (haqorat), defamation (tuhmat), and other contentious languages, analyzing speech and text’s semantic, syntactic, and pragmatic features. It highlights the methodological challenges of regional dialects, cultural idioms, and hierarchical social structures. Additionally, the study addresses the broader applications of forensic linguistics, including analyzing extremist materials, authorship disputes, and evaluating legal documents. Recommendations include establishing linguistic databases, training programs for forensic linguists, and policy reforms to enhance linguistic expertise in legal contexts. The findings underscore the vital role of forensic linguistics in ensuring fairness, accountability, and justice in Uzbekistan’s legal system, emphasizing the importance and impact of the field.
Abstract Understanding other people’s emotions accurately (i.e., empathic accuracy) is thought to be critical for building and maintaining social connections. Past research suggests empathic skills change with age, but few studies examine age differences in empathic accuracy within the context of close relationships. We examined whether empathic accuracy is higher among middle-aged couples (ages 40-50) compared to older couples (ages 60-70) using a sample of 154 heterosexual long-term marriages. Husbands and wives visited the laboratory and engaged in a 15-minute conversation on a topic of disagreement in their marriage. Conversations were video-recorded. Husbands and wives watched a video playback of their conversation twice, each time continuously rating either their own or their spouse’s emotional valence during the conversation using a rating dial that ranged from “very negative” to “very positive”. These continuous valence ratings were used to compute each spouse’s empathic accuracy as the strength of the correlation between their ratings of their spouse’s emotions and their spouse’s own self- ratings. Results revealed that age was not associated with husbands’ empathic accuracy. In contrast, older wives had greater empathic accuracy compared to middle-aged wives (Mdiff =.19, p =.028). However, older adults had been married longer, and length of marriage also predicted women’s empathic accuracy. Findings suggest that older women are better able to track the changing valence of their husbands’ emotions, perhaps because they have more practice.
The article examines the scientific methodological foundations of thesauru research of literary texts. To this end, the formation of the concept of thesaurus and the meaning of the thesaurus method, the types of thesaurus dictionary and their main function are analyzed. The importance of the thesaurus research method in the study of literary texts is determined. The research used methods such as systematization, generalization, sorting, and formulation of the material. The article pays special attention to foreign and domestic thesaurus studies, analyzes the types of thesaurus dictionaries and their features. The article compares the thesaurus and a simple dictionary, identifies a number of optimal moments and ineffective aspects of the thesaurus. In the article, the thesaurus is recognized as a special terminological dictionary within a particular subject area, the meanings of which are close to terms (words and phrases) and semantic relations between them and grouped into concepts. The thesaurus analysis method is also an important research method in modern literary science. The thesaurus research method is widely used in the analysis of literary texts, as it allows you to identify semantic connections between words and understand the meaning of a work, helps to analyze and classify words, create dictionaries and lexical databases. The results achieved in the course of the study can be used in thesaurus research, the construction of a thesaurus based on literary texts.
With the advent of the information age, the massive increase of English text data puts forward higher requirements for text analysis and processing. The aim of this study is to accurately evaluate the semantic complexity of English text through an autoencoder structure based on bidirectional attention. This paper first analyzes the importance of automatic classification of semantic complexity in English text, and then builds an autoencoder structure based on bidirectional attention, which captures bidirectional information in text, and then uses the autoencoder structure for feature extraction and dimension reduction, which further strengthens the model’s ability to capture semantic complexity. Finally, A Bidirectional Attention Self-Encoding English Text Semantic Complexity Automatic Grading Model (BSETG) is established. This study conducted experimental verification based on semantic Evaluation (SemEval) dataset, convolutional neural network (CNN)/Daily Mail dataset and Penn Treebank dataset, and conducted a comparative analysis with existing semantic complexity evaluation methods. The experimental results show that the overall accuracy of BSETG algorithm is maintained between 70% and 90%, the response speed of BSETG algorithm is relatively fast, and the success rate of BSETG algorithm is relatively stable to a large extent.
This research aims to analyze and determine 1) the role of digital technology in lexicology research, 2) a digital lexicography system for Arabic, and 3) the benefits and challenges of digitizing Arabic lexicology. The research method that researchers use is qualitative research with a library study type of research. The results of this research are: 1) Digital technology has had a significant impact on lexicology research, increasing efficiency, accessibility, and collaboration. With advanced tools and techniques like N.L.P., machine learning, and cloud storage, lexicology researchers can collect, analyze, and disseminate data more effectively and innovatively, enriching researchers' understanding of the language. 2) The digital lexicography system for Arabic consists of various technological components that combine to provide comprehensive and easily accessible linguistic information, such as utilizing digital corpora, lexical databases, N.L.P. tools, intuitive user interfaces, mobile applications, and data visualization tools. 3) Digitization of Arabic lexicology offers excellent benefits in terms of accessibility, research efficiency, data updates, collaboration, and visualization. However, challenges such as dialect diversity, data quality, technology infrastructure, data security, language complexity, and technology education need to be addressed to maximize the potential of this digitalization.
As the discussion of neology has expanded, various vocabulary and expressions have been added to the category of neology. Thus, the category of neology has been expanded. In this study, we propose ‘trending expressions’ as a broader concept than ‘neology’ or ‘memes’, which are the subject of today’s research. Accordingly, we define trending expressions based on the common characteristics of trending expressions and classify them according to their types. The most basic characteristic of trending expressions is ‘virality’, which means that they have a certain level of public recognition. In addition, trending expressions that are popular today are usually ‘deviant’ in the sense that they deviate from existing expressions, linguistic norms, or common sense in order to achieve novelty, and the deviant nature of trending expressions gives some trending expressions a cryptic character. Finally, these expressions are ‘playful’ in the sense that the use of language in and of itself creates a sense of satisfaction for the speaker. In this study, we categorize trending expressions into word-level trending expressions, phrase-level trending expressions, sentence-level trending expressions, sentence-plus trending expressions, and phrase-plus trending expressions according to their size, and provide examples of trending expressions belonging to each type. In addition, according to the kind of meaning they have, trending expressions are categorized into those that indicate new concepts, those that have specific discourse functions, and those that are simply used for entertainment.
Wearable devices often struggle to capture the full range of emotions accurately through peripheral physiological signals like Electrodermal Activity (EDA), Photoplethysmogram (PPG), and Electromyogram (EMG), leading to reduced classification accuracy. While Electroencephalogram (EEG) signals are recognized for their superior emotion detection capabilities, past EEG-based studies have been confined to lab settings with high-end systems using 32-64 channels. There is a growing need for systems that can continuously monitor emotions outside the lab. Modern wearable EEG devices, with configurations from single to eight channels, offer a solution. Our study investigates if integrating EEG data from only two channels in commercial wearable EEG devices with peripheral signals can enhance emotion detection accuracy. Using the publicly available DEAP dataset, which provides EEG and peripheral signals from 32 participants exposed to emotional stimuli, we explore various preprocessing and feature extraction techniques for multimodal emotion detection. The DEAP dataset categorizes emotions based on valence and arousal ratings, converting them into binary class problems: High Valence vs. Low Valence and High Arousal vs. Low Arousal. Intra-class emotion classification is performed using a Random Forest classifier with $\mathbf{5}$-fold cross-validation. Results show that while single-modality peripheral signals achieve classification accuracies of 76-85%, the addition of EEG data significantly boosts accuracy up to $\mathbf{9 5 \%}$. Combining EEG data with peripheral signals also greatly improves individual subject valence and arousal classification accuracy and F1 scores.
This article explores creative processes in discourse and language. As a starting point, the notion of linguistic creativity is regarded in relation to that of the linguistic norm. The main focus is on the description of the method of parametrization of linguistic creativity and the results of its application. This method is based on a three-level system of parameters. The macro-, micro-, and interdiscourse parameters composing this system facilitate the identification of creative use of language units in different types of discourse (such as media discourse, artistic discourse, advertising discourse, etc.). The study is based on the material from a functional electronic corpus of texts, which encompasses English -language films and their literary sources published from the 1960s to the present day. The article reveals variants of using the method of parametrization and principles of distinguishing cases of non-creative and creative exploitation of linguistic means in cinematic discourse. According to research findings, the creative or non-creative character of a particular language unit is determined by one of the two main purposes of its use in films. If a linguistic unit is used to create the impression of natural communication (the so-called artistic-aesthetic stylization), its use is qualified as non-creative. If a linguistic unit realizes certain aesthetic and pragmatic tasks in a film, its use is creative. The elaborated method of parametrization can be applied to any type of discourse. It detects ‘hotspots’ of changes in the state of a particular language and gives these changes a systematic linguistic assessment.
This community service activity aimed to socialize the correct (standard) use of the Indonesian language, thereby fostering a sense of love for the country among students at SMA Negeri 1 Cinangka, Serang Regency, Banten. The goal of this activity was to instill early awareness among students to use the Indonesian language according to standardized spelling with deep love for the nation, without feeling ashamed, outdated, or merely using it as a form of identity as Indonesian citizens. It sought to rekindle a sense of nationalism in the students of SMAN 1 Cinangka by encouraging them to love and use the Indonesian language in accordance with linguistic norms.The method used in the socialization activity involved preparation, implementation, evaluation, and reporting. The socialization event was held at SMA Negeri 1 Cinangka, Cinangka Village, Serang Regency, on Monday, August 26, 2024. The participants of this activity included 207 students from SMA Negeri 1 Cinangka and the KKM (Kuliah Kerja Mahasiswa) group 38 of Cinangka. The speakers were lecturers from Bina Bangsa University with a background in the field of linguistics. The results of this activity produced an understanding and awareness among students to use the Indonesian language according to standardized spelling with deep love for the nation, without feeling ashamed, outdated, or merely using it as a form of identity as Indonesian citizens. This socialization activity is expected to rekindle a sense of nationalism in the students of SMAN 1 Cinangka, encouraging them to love and use the Indonesian language in accordance with linguistic norms.
Locality and Interference are two mechanisms which are attested to drive sentence comprehension. However, the relationship between them remains unclear---are they alternative explanations or do they operate independently? To answer this question, we test the hypothesis that in Hindi, interference effects (measured by semantic similarity and case markers) significantly predict locality effects (modelled using dependency length quantifying distance between syntactic heads and their dependents) within a sentence, while controlling for expectation-based measures and discourse givenness. Using data from the Hindi-Urdu Treebank corpus (HUTB), we validate the stated hypothesis. We demonstrate that sentences with longer dependency length consistently have semantically similar preverbal dependents, more case markers, greater syntactic surprisal, and violate intra-sentential givenness considerations. Overall, our findings point towards the conclusion that locality effects are reducible to broader memory interference effects rather than being distinct manifestations of locality in syntax. Finally, we discuss the implications of our findings for the theories of interference in comprehension.
An acute bout of exercise in the moments after learning benefits the retention of new memories. This finding can be explained, at least partly, through a consolidation account: exercise provides a physiological state that is conducive to the early stabilisation of labile new memories, which supports their retention and subsequent retrieval. The modification of consolidation through non-invasive exercise interventions offers great applied potential. However, it remains poorly understood whether effects of exercise translate from the laboratory to naturalistic settings and whether the intensity of exercise determines the effect in memory. To this end, adult endurance runners were recruited as participants and completed two study sessions spaced two weeks apart. In each session, participants were presented with a list of words and asked to recall them on three occasions: (i) immediately following their presentation, (ii) after a 30-minute retention interval, and (iii) after 24 hours. Crucially, the 30-minute retention interval comprised our experimental manipulation: higher intensity exercise (running) in the first session and lower intensity exercise (walking) in the second, both completed in a naturalistic setting around participants' existing physical activity training programmes. Exertion was recorded through heart rate and rate of perceived exertion data. Alertness, mood, and arousal ratings were also collected before and after the 30-minute retention interval. Immediate memory for the two wordlists was matched, but participants retained significantly more words after 30 minutes and 24 hours when encoding was followed by higher than lower intensity exercise. Exertion data revealed that participants experienced vigorous and light exercise in the higher and lower intensity conditions, respectively. Significant improvements in alertness, mood, and arousal were observed following both exercise conditions, but especially in the higher intensity condition. These outcomes reveal that experiencing higher intensity physical activity in the field is conducive to declarative memory retention, possibly because it encourages consolidation.
Elitzur (2018a) examines the occurrence of abstract nouns ending in -ūt in the Masoretic tradition of the Hebrew Bible, noting a distinct pattern that distinguishes the Pentateuch from other biblical texts. His analysis highlights that these nouns are relatively rare in the Pentateuch and often written defectively, while they are more frequent and usually spelled plene (with waw) in the Prophets and Writings. Elitzur investigates specific examples such as גַּבְלֻת ‘twistedness’ and עֵדֻת ‘testimony’ to support this observation. He raises the question of whether the defective spelling in the Pentateuch signifies a historical mismatch between written and spoken forms or if many words with defective -ūt originally ended with a different suffix, later adapted under changing linguistic norms. Building on and extending Elitzur’s study, the discussion reveals the complexities of diachrony in Hebrew, particularly regarding the -ūt endings, which are often deemed characteristic of later forms of the language. Cohen (2012) has challenged this characterisation, arguing that their distribution is comparable within both the Torah and later texts. The chapter problematises this viewpoint, suggesting that the focus should be on the frequency of tokens rather than on mere number of lexemes. Among other things, it is pointed out that the orthographic discrepancies in the usage of -ūt in the Torah could reflect underlying morphological differences, i.e., that they might represent a later reinterpretation of forms that originally had different suffixes. Ultimately, the evidence suggests a complex interplay between orthography and morphology, underscoring the challenges in tracing the historical development of these noun forms in biblical Hebrew.
This paper explores null elements in English, Chinese, and Korean Penn treebanks. Null elements contain important syntactic and semantic information, yet they have typically been treated as entities to be removed during language processing tasks, particularly in constituency parsing. Thus, we work towards the removal and, in particular, the restoration of null elements in parse trees. We focus on expanding a rule-based approach utilizing linguistic context information to Chinese, as rule based approaches have historically only been applied to English. We also worked to conduct neural experiments with a language agnostic sequence-to-sequence model to recover null elements for English (PTB), Chinese (CTB) and Korean (KTB). To the best of the authors' knowledge, null elements in three different languages have been explored and compared for the first time. In expanding a rule based approach to Chinese, we achieved an overall F1 score of 80.00, which is comparable to past results in the CTB. In our neural experiments we achieved F1 scores up to 90.94, 85.38 and 88.79 for English, Chinese, and Korean respectively with functional labels.
In this paper, we aimed to develop a neural parser for Vietnamese based on simplified Head-Driven Phrase Structure Grammar (HPSG). The existing corpora, VietTreebank and VnDT, had around 15% of constituency and dependency tree pairs that did not adhere to simplified HPSG rules. To attempt to address the issue of the corpora not adhering to simplified HPSG rules, we randomly permuted samples from the training and development sets to make them compliant with simplified HPSG. We then modified the first simplified HPSG Neural Parser for the Penn Treebank by replacing it with the PhoBERT or XLM-RoBERTa models, which can encode Vietnamese texts. We conducted experiments on our modified VietTreebank and VnDT corpora. Our extensive experiments showed that the simplified HPSG Neural Parser achieved a new state-of-the-art F-score of 82% for constituency parsing when using the same predicted part-of-speech (POS) tags as the self-attentive constituency parser. Additionally, it outperformed previous studies in dependency parsing with a higher Unlabeled Attachment Score (UAS). However, our parser obtained lower Labeled Attachment Score (LAS) scores likely due to our focus on arc permutation without changing the original labels, as we did not consult with a linguistic expert. Lastly, the research findings of this paper suggest that simplified HPSG should be given more attention to linguistic expert when developing treebanks for Vietnamese natural language processing.
This paper aims to denaturalize the norm that Japanese first-person pronouns are gendered by analyzing why and how this norm was constructed from a historical discourse perspective. Focusing on two time periods, the early modernization era of the late nineteenth century and the wartime era of the first half of the twentieth century, the paper analyzes metapragmatic discourses found in the writings of linguists and intellectuals and in grammar books and school readers. Four main findings emerge, all of them related to the sexist nationalist ideologies that defined both periods. First, in the modernization era, nationalist ideologies promoted the construction of a national language, of which males were assumed to be the primary speakers. Second, this assumption legitimated linguists' practices of including masculinized pronouns and excluding feminized pronouns from the national language, such that gender-neutral watakushi and watashi and masculinized boku became the standard first-person pronouns, while no feminized pronoun was considered a standard form. Third, in Japan's linguistic colonization of East Asia during the wartime era, linguistic gender differences were highlighted as evidence of the superiority of the Japanese language. Fourth, to emphasize such linguistic gender differences, females' use of the masculinized pronoun boku was proscribed, while the norm of distinct gendered pronouns—especially watashi for females and boku for males—was gradually confirmed. These findings illustrate the importance of examining metapragmatic discourses from the diachronic perspective to deconstruct naturalized linguistic norms.
The cultural heritage (CH) domain possesses large volumes, necessitating users to provide more precise details regarding their requirements. Nonetheless, several formidable challenges are observed by the CH information retrieval researchers, including vocabulary issues and access points. Hence, an increasing demand for models capable of addressing these issues and professional search systems are required. These models enable users to search efficiently inside the CH domain. Many non-experts among its users are also typically attracted by CH content, necessitating improved access models to these rich contents. Therefore, this study investigated a terminologies synonym expansion (TSE) model for CH content. The proposed model combined three elements in the framework: TextRank algorithm capacity for terminology identification, comprehensive WordNet lexical database for synonym expansion, and synonym linking to their respective terminologies. Consequently, two CH collections (CHiC2013 and CHiC2013_EDE) demonstrated a noteworthy enhancement compared to the traditional information retrieval methods. This model could bridge the vocabulary disparity between non-expert users and the specialised terminology employed in the CH domain.
Over 15 years ago, Ward and Birner (2006) suggested that non-canonical constructions in English can serve both to mark information status and to structure the information flow of discourse.One such construction is preposing, where a phrasal constituent appears to the left of its canonical position, typically sentenceinitially.But computational work on discourse has, to date, ignored non-canonical syntax.We take account of non-canonical syntax by providing quantitative evidence relating NP/PP preposing to discourse relations.The evidence comes from an LLM mask-filling task that compares the predictions when a mask is inserted between the arguments of an implicit intersentential discourse relation -first, when the right-hand argument (Arg2) starts with a preposed constituent, and again, when that constituent is in canonical (post-verbal) position.Results show that (1) the top-ranked maskfillers in the preposed case agree more often with "gold" annotations in the Penn Discourse TreeBank (Webber et al., 2019) than they do in the latter case, and (2) preposing in Arg2 can affect the distribution of discourse-relational senses.
This study explores the phonological transformations that occur when foreign words, particularly English, are adopted into Indonesian. Employing a descriptive method, the research systematically examines how these words undergo changes and how their phonemes are altered during the adoption process. Using a linguistic approach combined with simple descriptive analysis, the study successfully analyzed a variety of borrowed words to uncover patterns in their phonological adaptation. The findings reveal that the adoption process often involves phonological addition, deletion, or retention of specific phonemes. Some phonemes remain constant, preserving their original sound, while others are either added or omitted to align with Indonesian phonological rules and linguistic norms. Notably, the study identifies and formulates about sixteen distinct patterns of phonological addition and deletion that regularly occur during this process. These patterns highlight the systematic nature of language adaptation, demonstrating how linguistic structures accommodate borrowed words to fit the phonological and phonetic framework of the target language. This research contributes valuable insights into the dynamic interaction between languages, particularly the way phonological structures are modified to ensure compatibility and ease of use in a new linguistic environment. These findings provide a foundational understanding of word adoption mechanics, enriching linguistic studies on loanwords and their impact on language evolution, particularly in Indonesian. The established formulas offer a structured perspective for further research in phonological adaptation and cross-linguistic influence.
Importance. The characteristics of the concepts “linguistic errors” and “linguistic norm” (subjective and objective) in the process of teaching native and foreign languages are given, which determines the significance of work in the modern multicultural space. The definitions of “speech culture” and “usus” are considered, and a typology of speech errors is described, which is divided according to aspects of the language: phonetics, grammar and vocabulary (stylistics). Research Methods. Examples of speech errors by French speakers are presented and analyzed based on the analysis of statistical data conducted by the French publications Le Figaro, Le Conseil Rédaction, Toploc, which clearly demonstrate how the language norm manifests itself and works. Results and Discussion. The conditions for describing the comparative and comparative analysis of contacting languages are substantiated as an important condition for identifying language difficulties and errors in language structures for the further application of this knowledge in the methodology of teaching both the native language and French and other foreign languages. Conclusion. The knowledge gained will allow students to improve their sociolinguistic competencies in the future, and the results of the study can be used in revising existing programs for the French language and organizing training in a more detailed consideration of the methodological support for teaching French: creating teaching aids, developing video materials and control.
Adequacy of Translation of English Phraseologisms Summary All languages of the world are rich in phraseological combinations, having a special vocabulary composition and constructive structure. Phraseological phrases as one of the unified linguistic universals remain an actual object of study in various fields of science – lexicology, grammar, stylistics, phonetics, language history, philosophy, logic, country studies and, of course, translation studies. The analysis of the problems of translating phraseological units from a theoretical point of view comes to the conclusion that the semantics of stable combinations reflects a number of spectral-logical meanings and connotative components. In the process of translation, the national-ethnic component of phraseological units, their imagery, which represent an information and expressive complex, create the integrity of the content, emotional, expressive, national-cultural associations, is taken as a basis. Adequate translation of phraseological expressions becomes possible when a pragmatically chosen expression, without violating linguistic norms, reflects the mentality and national-cultural values of native speakers. In the process of translation it is necessary to take into account the semantic meaning of phraseological expressions, their in-depth analysis, interlingual equivalence. Adequacy is the way to an optimal translation, the way of finding an optimal translation solution and, therefore, it is a translation process that can result in an equivalent translation. Thus, in order to create an equivalent translation, the translator selects an adequate translation method. Key words: Phraseological meaning, phraseological equivalence, semantic structure, adequate translation
BACKGROUND: Naming test are a very common tool in neuropsychological batteries. Some years ago, the Argentinean Psycholinguistic Naming test was developed, first with black and white drawings (Manoiloff et al., 2018) and then in colors (PAPDIC) (Vivas et al., 2020). Items were selected and organized on the basis of Argentinean psycholinguistic norms. At that time evidence of validity was reported (concurrent validity and contrasted groups analyses). Here we present new psychometric analysis and normative data for the Argentine population. METHOD: The sample comprised 292 participants: 195 healthy, 70 MCI, 14 stroke patients without aphasia and 13 stroke patients with aphasia. They went through a complete neuropsychological battery to ensure that no other cognitive function alteration (apart from language) could interfere with the task. Items were rated as dichotomous responses, and the final score only included those correct responses given before the phonological cue. RESULT: o assess the test's internal consistency a KR20 analysis was performed (as items were dichotomous) which showed a value of.879. Besides, a one factor ANOVA was performed to compare the full test score between groups and significant differences were observed (F(3,288) = 51.867; p <.001). Particularly, healthy participants differentiate from the MCI (p <.001) and stroke with aphasia (p <.001) groups, but no with stroke patients without aphasia (p =.133). Another comparison was performed between this version of the test and a previous black and white version by a chi-squared analysis with each item, and it showed a similar performance for 24 items, a better performance in the color version for 5 items and a worse performance in one item. Additionally, a regression analysis was performed in order to obtain normative data for the Argentine population. As age was the only demographic variable that showed significant effect on the test score (R2 adjusted =.140; F(1,192) = 32.545; p <.001), it was considered for this calculus. CONCLUSION: These results show that the PAPDIC is a reliable naming test for the Argentine population that can be used both for patients with neurodegenerative diseases and post stroke aphasia.
Within the brain, complex neurocircuitry integrates an array of signals to regulate postganglionic sympathetic neural discharge patterns. Recently, there has been increased interest in understanding the complexities of the central neural determinants of muscle sympathetic nerve activity (MSNA) in humans (Macefield & Henderson, 2019). Through the new technique of MSNA-coupled functional magnetic resonance imaging, activity within several cortical and subcortical structures, many of which are sites of central adrenergic innervation, have been shown to correspond to MSNA bursts (Macefield & Henderson, 2019). These findings are particularly relevant to clinical populations in whom central adrenergic and peripheral sympathetic dysregulation are concurrent, such as in individuals with chronic anxiety-related disorders (Bigalke & Carter, 2021). Moreover, previous studies have not investigated the influence of cortical structures on underlying postganglionic recruitment patterns, which might be a more sensitive measure of sympathetic dysregulation in comparison to traditional integrated MSNA assessment in these clinical populations (Bigalke & Carter, 2021). Disentangling the central regions involved in peripheral sympathetic postganglionic governance is a necessary step to provide mechanistic insight into therapeutic targets for populations with central and peripheral sympathetic dysregulation. In a recent study published in The Journal of Physiology, Klassen et al. (2024) investigated the impact of central adrenergic activity on peripheral sympathetic outflow in humans using two new approaches: (i) pharmacological activation of central α2-adrenergic receptors; and (ii) quantification of sympathetic neuronal subpopulation recruitment patterns using advanced action potential (AP) clustering analysis (Klassen et al., 2024; Yoo et al., 2020). Central α2-adrenergic receptors are primarily inhibitory, thus evoking a sympatholytic effect within the brain. The authors sought to examine the effects of central α2-adrenergic agonism on microneurographic recordings of MSNA and hypothesized that infusion of dexmedetomidine, an α2-adrenergic receptor agonist, would: (i) attenuate sympathetic AP discharge and recruitment; and (ii) reduce AP latency through inhibition of slower-conducting adrenergic neurons. To test their hypotheses, continuous blood pressure, heart rate and MSNA recordings were obtained in eight healthy individuals (three males and five females) throughout a baseline period and subsequent intravenous dexmedetomidine hydrochloride (i.e. α2-adrenergic agonist) infusion. Uniform reductions in blood pressure and integrated MSNA were observed following dexmedetomidine infusion, and these reductions were primarily attributable to ordered de-recruitment of large APs (which generally exhibit a low probability of firing), followed by highly active, medium-sized APs. It might be expected that de-recruitment of large APs would result in prolonged AP latency, but the opposite was observed (i.e. reduced time delay). As alluded to by Klassen et al. (2024), this might represent a direct impact of central α2-adrenergic activity on the temporal coding of sympathetic fibres. The authors observed a downward shift in the inverse relationship between AP cluster size and latency during dexmedetomidine infusion, supporting their interpretation of a direct impact of α2-agonism on central processing latencies or synaptic delays. However, the data also indicated that AP incidence was reduced primarily in the normalized AP clusters 1−3, while it remained unchanged in clusters 4 and 5 (fig. 5 of Klassen et al. 2024). This ordered de-recruitment might inadvertently have led to a more proportionate contribution of each AP cluster (including larger AP clusters) to the overall number of APs, whereas, in the absence of α2-adrenergic agonism, most APs are medium in size, with longer latencies. This equal contribution of AP clusters following α2-agonism to the calculated latency might also explain, in part, the reduction in AP latency. Participants also performed a Valsalva manoeuvre (VM), which provides a dynamic assessment of baroreflex regulation of peripheral sympathetic outflow. The reduction observed in postganglionic sympathetic discharge at rest was also evident during the VM. Furthermore, the discharge probability of medium-sized APs and the recruitment of larger APs was decreased during the VM despite significant blood pressure reductions. However, the VM-evoked reduction in AP latency was not altered by dexmedetomidine, although dynamic sympathetic AP baroreflex gain for medium-sized APs was attenuated. Thus, the authors reasonably speculate that mechanisms involving cortical command contribute to reductions in AP latency during the VM and function independently from baroreflex and α2-adrenergic mechanisms. Collectively, these findings suggest a complex relationship between higher cortical command, α2-adrenergic influences and baroreflex-mediated mechanisms that control postganglionic sympathetic discharge during physiological stress in humans. Dexmedetomidine can cause sedation, resulting in significant effects on consciousness. Levels of consciousness exert a profound impact on cardiovascular measures and sympathetic outflow (Somers et al., 1993). In the study by Klassen et al. (2024), sedation was monitored using the Ramsey scale and a visual analog scale ranging from 0 (very alert) to 100 (very sedated). At the end of the dexmedetomidine infusion, the participants were scored 3 (i.e. asleep, with brisk response to a loud voice) on the Ramsey scale and provided a visual analog scale arousal rating of 78 units, indicating apparent sedation. In prior studies in which microneurography was performed during sleep, a significant reduction in both blood pressure and MSNA was observed through progressively deeper stages of non-rapid eye movement (Somers et al., 1993). A Ramsey scale rating of 3 can be compared most aptly to early stages (i.e. stage I and II) of non-rapid eye movement sleep, in which participants generally exhibit abrupt awakening and responsiveness to loud perturbation and during which small reductions in blood pressure and integrated MSNA are observed (Somers et al., 1993). It is possible that a portion of the present alterations in AP cluster recruitment patterns is attributable to reduced levels of consciousness. However, evidence of an independent effect of α2-agonism on AP discharge and recruitment is bolstered by the fact that participants were fully conscious and able to maintain the necessary expiratory pressure to complete the 20 s VM, during which significant reductions in AP discharge remained apparent relative to baseline (Klassen et al., 2024). Given that AP discharge patterns during sleep in humans have not yet been assessed, it is difficult to state with certainty what proportion of the observed sympathoinhibition might be attributed to sedation levels, although the careful experimental design used by the research team strengthens a key role for α2-adrenergic activity on the observed sympathoinhibition independent of sedation levels. The findings of Klassen & colleagues (2024) might be extrapolated to inform sympathetic regulatory patterns in other clinical populations. In addition to their presence within the brainstem, α2-adrenergic receptors are expressed in numerous higher cortical areas (i.e. insular, cingulate and prefrontal cortices). Prior studies have suggested an association between activity within areas including the prefrontal, insular and anterior cingulate cortices and peripheral sympathetic outflow (Macefield & Henderson, 2019). Dysregulation within many of these brain regions has also been implicated in the pathogenesis of anxiety and stress-related disorders, populations in whom cardiovascular risk is elevated, probably owing to sympathetic dysregulation (Bigalke & Carter, 2021). Notably, although resting integrated MSNA appears largely unchanged across anxiety-related disorders in comparison to healthy control subjects, alterations in MSNA burst strength, single-unit activity and AP recruitment strategies have been reported in populations with generalized anxiety disorder, panic disorder and post-traumatic stress disorder (PTSD) (Bigalke & Carter, 2021). Yoo et al. (2020) were the first to investigate sympathetic AP recruitment patterns in a population of women with PTSD using similar analyses to that in the study by Klassen et al. (2024). The authors observed a significant elevation in AP discharge at rest, in addition to an augmented firing rate and exaggerated AP recruitment in response to cold pressor stress in women with PTSD in comparison to women without PTSD. This elevated sympathetic recruitment in response to stress was attributed to an increase in the firing frequency of low-threshold axons and the increased recruitment of dormant, larger-diameter axons within the sympathetic nervous system. The pathological sympathetic postganglionic discharge patterns in adults with PTSD (i.e. increased AP firing frequency and exaggerated recruitment of larger axons) (Yoo et al., 2020) appears to mirror inversely the discharge patterns following α2-agonism via dexmedetomidine infusion (i.e. reduced AP firing frequency and de-recruitment of large axons) (Klassen et al., 2024), suggesting a potential role for central α2-adrenergic dysfunction underlying sympathetic dysregulation present in anxiety/stress-related disorders (Bigalke & Carter, 2021) (Fig. 1). Notably, a core diagnostic feature of PTSD among other anxiety-related disorders is hyperarousal, which is characterized by symptoms such as irritability, sleep disturbances and agitation. Increased central adrenergic activity within the aforementioned brain regions has been implicated in the pathophysiology of hyperarousal and has been suggested to underlie the symptomology associated with these disorders. This notion is supported by the use of α2-adrenergic receptor agonists, such as clonidine, to reduce central adrenergic activity and alleviate symptoms such as nightmares within individuals with PTSD. Extrapolation of the findings of Klassen et al. (2024) might suggest that the beneficial effects of α2-agonists on the symptomology of chronic anxiety/stress related disorders is attributable, in part, to reduced sympathetic hyperarousal, and also that α2-agonism might provide the dual benefit of reducing sympathetic hyperactivity and cardiovascular risk in these populations (Fig. 1; Yoo et al., 2020; Bigalke & Carter, 2021). In summary, Klassen & colleagues (2024) are the first to provide an elegant characterization of the influence of central α2-adrenergic mechanisms on sympathetic postganglionic discharge patterns and governance. These findings support a clear sympatho-inhibitory role of central α2-adrenergic activity mediated through ordered de-recruitment of peripheral sympathetic neurons. This study improves our knowledge surrounding the neural correlates of peripheral sympathetic outflow in humans and provides the basis for future investigation into the role that α2-adrenergic receptors might have in the observed peripheral sympathetic dysregulation in populations with central adrenergic dysregulation. Please note: The publisher is not responsible for the content or functionality of any supporting information supplied by the authors. Any queries (other than missing content) should be directed to the corresponding author for the article. The authors declare that they have no competing interests. All authors have approved the final version of the manuscript. All authors agree to accountability for the present work. All authors contributed significantly to the present work. None. We thank Drs Manda Keller-Ross, Ida Fonkoue and Jason Carter for their helpful feedback and assistance in manuscript preparation.
This article analyzes the development of English in the epoch of globalization, the evolutionary changes causing the appearance of new variants of English, and the functions of English in social life. Moreover, it deals with the rapid spread of English, which is believed to be one of the main tendencies of globalization This study offers an insight into the problem of English language variation. We also discuss the criteria to define both local variants and Global English and perspectives of their development. Globalization has led to the widespread use of English as the language of international communication (Lingua Franca), which facilitates communication between people from different cultures and countries. The dominance of English is due to the influence of English-speaking economies, technologies, and its role in education and science, where English has become the primary language for academic publications and research. This promotes cultural exchange, but also raises concerns about the possible displacement of local languages and cultures. Some researchers, in particular R. Phillipson, emphasize the risk of linguistic imperialism, when English reinforces the dominance of Western ideas and values. However, the spread of English as a Lingua Franca leads to its localization, producing different variants that reflect local cultures and needs. This adaptability allows English to integrate into different linguistic environments, although it creates new linguistic norms that differ from those of native speakers.
The contemporary western school, being one of the most important axes of social cohesion, plays a central role in the socialization between sexes, since it proposes tools for communication, as well as promoting interactions that involve language in its symbolic character. By gaining communicative competence, subjects acquire the capital to occupy a position in the field; however, it should be noted that not all species of capital are accepted. Some are legitimized by the type of individual who disputes them, others are simply rejected. Thus, learning language at school means learning the rules of official discourse and adapting to it; although it takes time, such learning is the possibility of gaining adhesion to a social group or obtaining upward social mobility; "adapting" to the linguistic norm has an implicit meaning, and that is to instrumentalize oneself discursively to achieve communicative ends. Language ceases to be a mother tongue, that is, the language of affections, to become a standard language, an instrument language. This chapter reflects on the phenomenon of school education, where non-sexist language and its associated behaviors are not yet seen as a prestigious capital that can be included in the curriculum, and it is thanks to the initiative of teachers, who are trained in the gender perspective, that these issues are addressed by incorporating more inclusive pedagogical communication strategies, where awareness in the use of language is one of the most relevant aspects in the process of building knowledge in the classroom.
Emotional stimuli are usually remembered with high confidence. Yet, it remains unknown whether—in addition to memory for the emotional stimulus itself—memory for a neutral stimulus encountered just after an emotional one can be enhanced. Further, little is known about the interplay between emotion elicited by a stimulus and emotion relating to affective dispositions. To address these questions, we examined (1) how emotional valence and arousal of a context image preceding a neutral item image affect memory of the item, and (2) how such memory modulation is affected by two hallmark features of emotional disorders: trait negative affect and tendency to worry. In two experiments, participants encoded a series of trials in which an emotional (negative, neutral, or positive) context image was followed by a neutral item image. In experiment 1 ( n = 42), items presented seconds after negative context images were remembered better and with greater confidence compared to those presented after neutral and positive ones. Arousal ratings of negative context images were higher compared to neutral and positive ones and the likelihood of correctly recognizing an item image was related to higher arousal of the context image. In experiment 2 ( n = 59), better item memory was related to lower trait negative affect. Participants with lower trait negative affect or tendency to worry displayed higher confidence compared to those with high negative affect or tendency to worry. Our findings describe an emotional “carry-over” effect elicited by a context image that enhances subsequent item memory on a trial-by-trial basis, however, not in individuals with high trait negative affect who seem to have a general memory disadvantage.
Effective communication through the medium of indigenous languages serves as an invaluable instrument that facilitates every language’s right to information during pandemics. Different online media outlets used Nigerian languages to disseminate information that could enhance the success of public health measures targeted at mitigating the impact of COVID-19. However, not all of the audience absorbed the messages positively. This study attempts to analyze the use of hate speech in the comments of readers of Hausa online news items on Legit Hausa and BBC Hausa that responded to news items on COVID-19. To achieve this, the readers' comments were purposively sampled and analyzed based on the pragmatic principles of politeness and peaceful communication. In addition, systemic functional grammar was used to explicate the grammatical features of the analyzed linguistic elements of the comments written in Hausa. It was found that the comments were not only replete with inflammatory language – stripping the users of the status of communicative humanizer – inimical to preventive measures against COVID-19 but also capable of widening the opinion divide. Furthermore, most comments analyzed flout the principles of Hausa spelling and sentence construction. The study thus recommends that linguistic activists should consistently advocate for the use of Nigerian languages that conform to linguistic norms and the principles of peaceful communication that would curtail misinformation and division in the course of pandemic control.
Abstract Syntactic parsing is one of the areas in Natural Language Processing. The development of large-scale multilingual language models has enabled cross-lingual parsing approaches, which allows us to develop parsers for languages that do not have treebanks available. However, these approaches rely on the assumption that languages share orthographic representations and lexical entries. In this article, we investigate methods for developing a dependency parser for Xibe, a low-resource language that is written in a unique script. We first investigate lexicalized monolingual dependency parsing experiments to examine the effectiveness of word, part-of-speech, and character embeddings as well as pre-trained language models. Results show that character embeddings can significantly improve performance, while pre-trained language models decrease performance since they do not recognize the Xibe script. We also train delexicalized monolingual models, which yield competitive results to the best lexicalized model. Since the monolingual models are trained on a very small training set, we also investigate lexicalized and delexicalized cross-lingual models. We use six closely related languages as source language, which cover a wide range of scripts. In this setting, the delexicalized models achieve higher performance than lexicalized models. A final experiment shows that we can increase performance of the cross-lingual model by combining source languages and selecting the most similar sentences to Xibe as training set. However, all cross-lingual parsing results are still considerably lower than the monolingual model. We attribute the low performance of cross-lingual methods to syntactic and annotation differences as well as to the impoverished input of Universal Dependency Part-of-Speech tags that the delexicalized model has access to.
We propose the Hyperbolic Tangent Exponential Linear Unit (TeLU), a neural network hidden activation function defined as TeLU(x)=xtanh(exp(x)). TeLU's design is grounded in the core principles of key activation functions, achieving strong convergence by closely approximating the identity function in its active region while effectively mitigating the vanishing gradient problem in its saturating region. Its simple formulation enhances computational efficiency, leading to improvements in scalability and convergence speed. Unlike many modern activation functions, TeLU seamlessly combines the simplicity and effectiveness of ReLU with the smoothness and analytic properties essential for learning stability in deep neural networks. TeLU's ability to mimic the behavior and optimal hyperparameter settings of ReLU, while introducing the benefits of smoothness and curvature, makes it an ideal drop-in replacement. Its analytic nature positions TeLU as a powerful universal approximator, enhancing both robustness and generalization across a multitude of experiments. We rigorously validate these claims through theoretical analysis and experimental validation, demonstrating TeLU's performance across challenging benchmarks; including ResNet18 on ImageNet, Dynamic-Pooling Transformers on Text8, and Recurrent Neural Networks (RNNs) on the Penn TreeBank dataset. These results highlight TeLU's potential to set a new standard in activation functions, driving more efficient and stable learning in deep neural networks, thereby accelerating scientific discoveries across various fields.
Activity and parameter sparsity are two standard methods of making neural networks computationally more efficient. Event-based architectures such as spiking neural networks (SNNs) naturally exhibit activity sparsity, and many methods exist to sparsify their connectivity by pruning weights. While the effect of weight pruning on feed-forward SNNs has been previously studied for computer vision tasks, the effects of pruning for complex sequence tasks like language modeling are less well studied since SNNs have traditionally struggled to achieve meaningful performance on these tasks. Using a recently published SNN-like architecture that works well on small-scale language modeling, we study the effects of weight pruning when combined with activity sparsity. Specifically, we study the tradeoff between the multiplicative efficiency gains the combination affords and its effect on task performance for language modeling. To dissect the effects of the two sparsities, we conduct a comparative analysis between densely activated models and sparsely activated event-based models across varying degrees of connectivity sparsity. We demonstrate that sparse activity and sparse connectivity complement each other without a proportional drop in task performance for an event-based neural network trained on the Penn Treebank and WikiText-2 language modeling datasets. Our results suggest sparsely connected event-based neural networks are promising candidates for effective and efficient sequence modeling.
Purpose: The general purpose of this study was to explore the impact of social media on language evolution. Methodology: The study adopted a desktop research methodology. Desk research refers to secondary data or that which can be collected without fieldwork. Desk research is basically involved in collecting data from existing resources hence it is often considered a low cost technique as compared to field research, as the main cost is involved in executive’s time, telephone charges and directories. Thus, the study relied on already published studies, reports and statistics. This secondary data was easily accessed through the online journals and library. Findings: The findings reveal that there exists a contextual and methodological gap relating to the impact of social media on language evolution. Preliminary empirical review revealed significant changes in language use driven by the rapid spread of new words, phrases, and communication styles on social media platforms. It found that social media democratized language change, allowing diverse users to influence linguistic trends, and highlighted the emergence of micro-languages within online communities. The integration of visual elements like emojis and memes into text-based communication added nuance and expressiveness, aligning digital interactions more closely with face-to-face communication. The study emphasized the need for digital literacy in education and ongoing research into digital communication's impact on language, noting social media's role as a powerful catalyst for language change. Unique Contribution to Theory, Practice and Policy: The Social Network Theory, Diffusion of Innovations Theory and Speech Community Theory may be used to anchor future studies on social media on language evolution. The study recommended expanding traditional linguistic theories to incorporate the dynamics of digital communication, incorporating digital literacy into education to prepare students for new linguistic norms, and for businesses to align their messaging with emerging social media trends. It also advised policymakers to use social media for language preservation, bridge the digital divide to promote linguistic diversity, and support interdisciplinary research to understand the long-term effects of social media on language. These recommendations aimed to adapt theory, practice, and policy to the evolving linguistic landscape.
Fine-tuning pre-trained language models for specific natural language processing tasks often leads to suboptimal performance due to the vast parameter space and the challenge of finding the most effective model configurations. Traditional fine-tuning methods can be computationally expensive and may not fully exploit the potential of these models, particularly for tasks like sentiment analysis. This work explores the application of metaheuristic techniques, focusing on sentiment analysis using the Stanford Sentiment Treebank 2 (SST2) dataset.We utilize two approaches: Genetic Algorithms (GA) and the Whale Optimization Algorithm (WOA). These methods aim to efficiently search the parameter space and optimize the fine-tuning process of pretrained language models. To enhance efficiency, we incorporate layer freezing techniques along with different crossover strategies. In the results obtained, GA with Simulated Binary Crossover (SBX) and 30% layer freezing achieved 94.02% accuracy, while WOA with SBX crossover and 30% layer freezing achieved 94.67% accuracy. These outcomes highlight the potential of integrating evolutionary algorithms, nature-inspired optimization techniques, and strategic layer freezing with deep learning finetuning processes for NLP tasks.
The administration of painful primes has been shown to influence the perception of successively presented semantic stimuli. Painful primes lead to more negative valence ratings of pain-related, negative, and positive words than no prime. This effect was greater for pain-related than negative words. The identities of this effect's neural correlates remain unknown. In this EEG experiment, 48 healthy subjects received noxious electrical stimuli of moderate intensity. During this priming, they were presented with adjectives of variable valence (pain-related, negative, positive, and neutral). The triggered event-related potentials were analyzed during N1 (120-180 ms), P2 (170-260 ms), P3 (300-350 ms), N400 (370-550 ms), and two late positive complex components (LPC1 [650-750 ms] and LPC2 [750-1000 ms]). Larger event-related potentials were found for negative and pain-related words compared to positive words in later components (N400, LPC1, and LPC2), mainly in the frontal regions. Early components (N1, P2) were less affected by the word category but were by the prime condition (N1 amplitude was smaller with than without painful stimulation, P2 amplitude was larger with than without painful stimulation). Later components (LPC1, LPC2) were not affected by the prime condition. An interaction effect involving prime and word category was found on the behavioral level but not the electrophysiological level. This finding indicates that the interaction effect does not directly translate from the behavioral to the electrophysiological level. Possible reasons for this discrepancy are discussed.
The teaching material of a student can come from anywhere, one of which is an oration text. In an oration text, it is necessary to pay attention to the quality of content, effective sentences, and language suitability. This research aims to know the quality of content and language suitability contained in the Mendikbudristek oration text on National Education Day 2023 for a tenth-grade SMA student's teaching material. The method used in this research is a qualitative descriptive method. This qualitative descriptive method is used to investigate and explain matters related to a fact that occurs in the surrounding environment. Additionally, the data analysis in the study is conducted using the method of agih. The method of agih is a method where the determining tool is part of the language concerned. The result of this research is that there are still several errors in the Mendikbudristek oration text on National Education Day 2023 and 2024, including spelling errors, incorrect words, and word economy. This causes some sentences to be ineffective and the information provided is not well conveyed to the reader. It is hoped that this research can provide knowledge to readers so that they can understand language rules and linguistic norms, thus ensuring that the purpose of the provided information is well conveyed to the public.
Augmented Reality (AR) technology has begun to significantly influence human interaction with language, particularly in English language use. Hence, this research examined the influence of Augmented Reality (AR) on communication patterns, the emergence of specialized AR-related language, and its impact on English language norms. For this purpose, 10 Students from the MA TEFL workshop at Allama Iqbal Open University, Islamabad, were selected to conduct detailed interviews. Interview data and its content were analyzed linguistically. These students were also teachers, so the data were used both ways. Through linguistic analysis, it was found that Augmented Reality (AR) significantly influences English language communication patterns by notable shifts in vocabulary, syntax, and discourse structures. Integrating AR-specific terms into everyday language among MA TEFL students signifies a transformative impact on linguistic norms, reflecting a deeper entwinement of language and technology. The study's findings recommended that language educators and curriculum developers should actively integrate AR technology and its associated linguistic elements into English language teaching and learning frameworks.
This paper analyzes the translation of “Xing Qing” in two seminal English versions of A Dream of Red Mansions by Yang Hsien-yi, Gladys Yang, and David Hawkes. It examines the translation strategies employed across different contexts using corpus analysis. The term “Xing Qing” is translated in three principal ways: literal translation, which faithfully replicates the characters’ personality traits; free translation, which adapts to specific situations and emotional contexts; and a version aligning with English linguistic norms. Yang’s translation tends toward literal fidelity, emphasizing the preservation of cultural nuances. In contrast, Hawkes’ approach is more flexible, favoring free translation and prioritizing reader engagement. The study argues that translators should select contextually appropriate strategies that convey the characters’ traits and emotions accurately and ensure both the translation’s fluidity and the retention of cultural information. This analysis underscores the importance of strategic choice in bal-ancing fidelity to the source text with the accessibility of the translation.
Abstract Naturalistic paradigms can assure ecological validity and yield novel insights in psychology and neuroscience. However, using behavioral experiments to obtain the human ratings necessary to analyze data collected with these paradigms is usually costly and time-consuming. Large language models like GPT have great potential for predicting human-like behavioral judgments. The current study evaluates the performance of GPT as a substitute for human judgments for affective dynamics in narratives. Our results revealed that GPT’s inference of hedonic valence dynamics is highly correlated with human affective perception. Moreover, the inferred neural activity based on GPT-derived valence ratings is similar to inferred neural activity based on human judgments, suggesting the potential of using GPT’s prediction as a reliable substitute for human judgments.
Summary While consumers are increasingly used to purchasing online, virtual reality (VR) is well acknowledged to enhance consumer experience via immersive and interaction systems. In our research, we recruited 160 participants (80 per experiment) to compare their consumer experiences of choosing Fast‐Moving Consumer Goods (FMCGs) in a virtual store ( via VR) and on an online webpage. Specifically, each participant was asked to choose four FMCGs (foods in Experiment 1 and non‐foods in Experiment 2) for the next 4 weeks, and they filled out the Positive and Negative Affect Scale before and after completing choice tasks. Results of the anova showed that there was a significant decrease in negative affect scores following both food and non‐food choices ( M before = 1.3 vs. M after = 1.2). Positive affect ratings were significantly higher for food choices in VR than online ( M VR = 2.5 vs. M online = 2.1), with no significant difference for non‐food choices. This highlights the impact of VR on food choice and its potential to transform human–food interactions. The study reveals that VR can narrow the gap between consumers' expectations and actual perceptions by creating an immersive and interactive shopping experience, thus significantly influencing consumer behaviour.
To analyze English discourse more accurately and provide more detailed feedback information, this study applies Rasch measurement and Conditional Random Field (CRF) models to English discourse analysis. The Rasch measurement model is widely used to evaluate and quantify the potential traits of individuals, and it has remarkable advantages in measurement and evaluation. By combining the CRF model, the Rasch model is employed to model the structural and semantic information in the discourse and use this model to carry out sequence labeling, to enhance the ability to capture the internal relations of the discourse. Finally, this study conducts comparative experiments on integrating the Rasch measurement and CRF models, comparing the outcomes against traditional scoring methods and the standalone CRF model. The research findings indicate that: (1) The discourse component syntactic analysis model on the Penn Treebank (PTB) database obtained Unlabeled Attachment Score (UAS) values of 94.07, 95.76, 95.67, and 95.43, and Labeled Attachment Score (LAS) values of 92.47, 92.33, 92.49, and 92.46 for the LOC, CRF, CRF2O, and MFVI models, respectively. After adding the Rasch measurement model, the UAS values of the four models on the PTB database are 96.85, 96.77, 96.92, and 96.78 for the LOC, CRF, CRF2O, and MFVI models, respectively, with LAS values of 95.33, 95.34, 95.39, and 95.32, all showing significant improvement. (2) By combining contextual information with CRF models, students can better understand their discourse expression, capture the connections between English discourse sentences, and analyze English discourse more comprehensively. This study provides new ideas and methods for researchers in English language education and linguistics.
This article is about Semantic Role Labeling for English partitive nouns (5%/REL of the price/ARG1; The price/ARG1 rose 5 percent/REL) in the NomBank annotated corpus. Several systems are described using traditional and transformer-based machine learning, as well as ensembling. Our highest scoring system achieves an F1 of 91.74% using "gold" parses from the Penn Treebank and 91.12% when using the Berkeley Neural parser. This research includes both classroom and experimental settings for system development.
Teaching English to university students requires a balance between fluency and accuracy.Both aspects are crucial for effective communication, but they serve slightly different purposes and should be addressed appropriately in a universitylevel English course.The paper explores the importance of accuracy and fluency in teaching and learning English and emphasises they are both essential components of mastering a foreign language.Teaching both accuracy and fluency requires a structured approach that addresses students' academic needs and prepares them for real-world communication.Within the scope of this paper, we focus on effective strategies for promoting and integrating fluency and accuracy in English language classrooms.Fluency and accuracy in language teaching are important since they complement each other.We believe it is necessary to foster fluency and accuracy in English language classrooms that result in higher levels of communicative competence.These two aspects help learners become effective communicators who can express themselves clearly and confidently while adhering to the linguistic norms of the language.The paper aims to provide the best ideas and effective practices to be implemented in an English language classroom: using authentic materials, providing constructive feedback, integrating task-based learning, and encouraging peer collaboration.The responsibility of every teacher is to develop a balanced and structured approach when every student gets a chance to work on fluency and accuracy.The teacher should provide constructive feedback that addresses both accuracy and fluency.By balancing the development of accuracy and fluency in English, university students can effectively communicate in academic settings and beyond, preparing them for future academic success and professional endeavours.