Papers reviewed and determined not to be word norm studies. Use the flag icon to report errors or suggest re-inclusion.
16504 papers
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.
In modern linguistics, there are no cases of comprehensive study of concepts, that is, the study of both theoretical and practical aspects. Thus, it is not an easy task to determine the ways of lexical expression of a certain concept. The purpose of this article is to identify stereotypes related to the concept of happiness in the linguistic culture of the Uzbek and English languages, to study the linguistic space, as well as to analyze some literary sources. This article is devoted to the linguacultural aspects of concept “happiness” in modern English and Uzbek languages. Furthermore, it is analyzed both as common value of humankind as well as cultural specify of some nation. Attitude to happiness allows revealing the existential characteristics, norms, traditions of different social groups, since a different interpretation of happiness within the framework of different cultures reveals their ethnos cultural specificity and perception of the world and people.
Gender-fair language has been the subject of much recent research and insufficient consideration has been given to the negotiations of inclusive linguistic norms in everyday interactions. We build on the concept of grassroots linguistic activism to propose that community norms and affiliation around shared values influence the use of gender-fair language. We test these expectations following a corpus-assisted discourse approach, analysing ten YouTube videos on sustainable period products and their comment sections. We focus on the highly cisgendered period discourse to explore the extent to which gender-fair language has infiltrated mainstream usage. We find great variation in the awareness of gender diversity in the data. Only when gender-fair language is used in the videos, trans and non-binary people openly participate in the commentary, suggesting that linguistic invisibility leads to actual exclusion. Shared communal values of inclusivity, on the other hand, form the basis of successful grassroots linguistic activism and foster change in language use.
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.
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 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.
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.
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 lexical and phraseological level of the language system is constantly in dynamics, reflecting the communicative needs of society. Changes in the socio-political life of recent decades have also caused a change in the attitude of native speakers of modern Russian to the language norm. The boundary between codified and uncodified speech is not always clear. This determines the active interaction of colloquial and slang speech. The increased expressiveness of oral speech causes people who use urban slang to need to transform the linguistic means they know, entailing their reduction and increasing the expressiveness of the utterance. Such processes contribute to the use of phraseological units as a means of expressive derivation. However, a free transition from communication involving slang units to communication within the framework of literary and colloquial speech can ensure that some of the reduced phraseological neologisms enter the circle of colloquial units, and then it is possible to continue the derivation process, as a result of which the language system can be enriched with a new lexical unit. Using the example of the phraseological neologism “na krainyak” (to the extreme), one can see the mechanism of action of phraseological reduction as an intermediate stage of expressive derivation.
Abstract Human creativity originates from brain cortical networks that are specialized in idea generation, processing, and evaluation. The concurrent verbalization of our inner thoughts during the execution of a design task enables the use of dynamic semantic networks as a tool for investigating, evaluating, and monitoring creative thought. The primary advantage of using lexical databases such as WordNet for reproducible information-theoretic quantification of convergence or divergence of design ideas in creative problem solving is the simultaneous handling of both words and meanings, which enables interpretation of the constructed dynamic semantic networks in terms of underlying functionally active brain cortical regions involved in concept comprehension and production. In this study, the quantitative dynamics of semantic measures computed with a moving time window is investigated empirically in the DTRS10 dataset with design review conversations and detected divergent thinking is shown to predict success of design ideas. Thus, dynamic semantic networks present an opportunity for real-time computer-assisted detection of critical events during creative problem solving, with the goal of employing this knowledge to artificially augment human creativity.
In the investigation of musical features that influence musical affect, timbre has received relatively little attention. Investigating affective timbres as they vary between instrument families can lead to inconsistent results, because one instrument family can produce a wide variety of timbres. Here, we consider timbre descriptors, as fine-grained acoustic representations of a sound. Using identical methods, we re-analyzed and synthesized results from three previously published studies: Eerola et al. (2012, Mus. Percept.), McAdams et al. (2017, Front. Psychol.), and Korsmit et al. (2023, Front. Psychol.). In doing so, we aimed to reveal robust timbre descriptors that consistently predict the affective response and to explain any discrepancies in results arising from differences in experimental methodology. We computed spectral, temporal, and spectro-temporal descriptors from all stimuli and used these to predict the affect ratings using linear and nonlinear methods. Our most consistent finding was that the fundamental frequency or higher-frequency energy of a sound predicted pleasant affect (i.e., positive valence, happiness, sadness) in one direction and unpleasant affect (i.e., tension, anger, fear) in the opposite direction. Clear discrepancies in previous findings may be attributable to differences in experimental design. When pitch variation was present in a stimulus set, energy arousal was predicted by pitch and inharmonicity, whereas when attack variation was present in the stimulus set, energy arousal was predicted by a faster attack and shorter sustain.
The paper focuses on the problem of language ecology in modern academic texts and analyses Russianlanguage scientific articles on construction and building. The study is relevant due to the need to establish linguoecological norms to improve the effectiveness of scientific communication. The study aims to identify the main linguistic and ecological problems of scientific text, i.e. lexical, grammatical, style errors, excessive nominalization, and syntactic complexity. The material of the study includes Russian-language scientific articles of the thematic area “Construction and Architecture” published in the journal “Bulletin of SUSU” in 2023. Linguotoxic elements can be traced both in the title complex, in the abstracts and full texts of research papers. The most characteristic linguoecological problems of scientific texts of this area are syntactic complexity, excessive nominalization, as well as cliches. The formation of linguoecological competence of a researcher will improve academic literacy and develop the culture of academic writing.
The aim of the study is to determine the quality of machine translation of English press releases into Russian in terms of semantic, stylistic and communicative adequacy. The article considers examples of communicative failures and analyses the reasons for the inadequacy of machine translation. The scientific novelty of the research consists in revealing violations of linguistic norms of the Russian language in the translated text of informative governmental press releases characterized by the high diplomatic style. The study found that communicative failures – violations of the norms of the Russian language – occur as a result of literal translation without analyzing the wider linguistic context, selection of an adequate meaning or significant translation transformations at the level of syntactic constructions, such as modulation, displacement, omission, addition, and others. Avoiding such communicative failures requires training of the machine translation system in the rules of the Russian language, English-Russian translation equivalents corresponding to the official business style, and replenishment of the language base.
Social decision-making is known to be influenced by predictive emotions or the perceived reciprocity of partners. However, the connection between emotion, decision-making, and contextual reciprocity remains less understood. Moreover, arguments suggest that emotional experiences within a social context can be better conceptualised as prosocial rather than basic emotions, necessitating the inclusion of two social dimensions: focus, the degree of an emotion's relevance to oneself or others, and dominance, the degree to which one feels in control of an emotion. For better representation, these dimensions should be considered alongside the interoceptive dimensions of valence and arousal. In an ultimatum game involving fair, moderate, and unfair offers, this online study measured the emotions of 476 participants using a multidimensional affective rating scale. Using unsupervised classification algorithms, we identified individual differences in decisions and emotional experiences. Certain individuals exhibited consistent levels of acceptance behaviours and emotions, while reciprocal individuals' acceptance behaviours and emotions followed external reward value structures. Furthermore, individuals with distinct emotional responses to partners exhibited unique economic responses to their emotions, with only the reciprocal group exhibiting sensitivity to dominance prediction errors. The study illustrates a context-specific model capable of subtyping populations engaged in social interaction and exhibiting heterogeneous mental states.
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.
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.
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.
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.
Code-mixing in movies is used to reflect human life and modernity in today’s bilingual or multilingual context. By studying the code-mixing in the movie, EFL learners can have better understanding on how language is used in different contexts and how it reflects societal norms and values. This qualitative research used content analysis to find out Hoffman’s code mixing within the dialogue of Disney’s Encanto. The result shows that code-mixing involving a change of pronunciation between Spanish and English occurs more than intra-lexical and intra-sentential code mixing. It happens because there are three characters who used Spanish accent in their dialogues. This study shows how language is used and represented in media. It also shows the media’s inclusion strategy to portray a more authentic and relatable cultures and communities.
The global dominance of English has transformed it into a dynamic, hybrid language enriched by contributions from non-native speakers. This paper investigates the integration of loanwords, grammatical structures, and narrative techniques from languages such as Spanish, French, Arabic, and Kurdish into English, emphasizing the role of non-native authors in reshaping its lexicon and syntax. Through a mixed-methods approach—combining corpus analysis, lexical examination, and discourse studies—the study reveals how linguistic borrowing reflects sociocultural exchanges and challenges traditional norms of "standard" English. Case studies of authors like Khaled Hosseini and Sheni A. Othman illustrate how multilingual narratives preserve cultural identity while innovating English literary expression. Findings indicate that loanwords often retain phonological and semantic traits of their source languages, with social media accelerating their adoption. Grammatical adaptations, such as syntactic calques and code-switching, further demonstrate the fluidity of English in multicultural contexts. The paper argues that non-native contributions foster linguistic diversity, though tensions persist between global intelligibility and local authenticity. By examining these phenomena, the study advocates for inclusive language policies that recognize non-native varieties as legitimate forms of English. Ultimately, this research underscores the transformative power of linguistic hybridity, positioning English as a living, evolving entity shaped by its global users rather than a static, monolithic system.
Traditional morphological methods have long been at the heart of Arabic language processing. They exploit the complex morphological structure of the language, characterized by roots, prefixes, infixes, and suffixes used for analyzing and generating words. These methods have been effective for tasks such as lemmatization, and rooting. However, they can be resource-intensive and do not always take semantics into account. Recent advancements in deep learning, particularly transformer-based models, offer new prospects for Arabic language processing. Despite their success in languages such as Turkish, Latin, English, and Slavic, to our knowledge, no transformer-based method has been implemented for the Arabic lemmatization task. In this study, we propose a transformer-based lemmatizer using T5, specifically AraT5, MT5, and BERT. We evaluate the models using the ArabicPADT UD Treebank corpus and benchmark their performance against standard metrics, including accuracy, precision, recall, and F1 score. Our results show an accuracy of $88.58 \%$, demonstrating competitive performance and highlighting the potential of transformer-based models for advancing Arabic lemmatization.
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.
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.
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.
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.
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.
A close relationship between emotional contagion and spontaneous facial mimicry has been theoretically proposed and is supported by empirical data. Facial expressions are essential in terms of both emotional and motor synchrony. Previous studies have demonstrated that trait emotional empathy enhanced spontaneous facial mimicry, but the relationship between autistic traits and spontaneous mimicry remained controversial. Moreover, previous studies presented faces that were static or videotaped, which may lack the "liveliness" of real-life social interactions. We addressed this limitation by using an image relay system to present live performances and pre-recorded videos of smiling or frowning dynamic facial expressions to 94 healthy female participants. We assessed their subjective experiential valence and arousal ratings to infer the amplitude of emotional contagion. We measured the electromyographic activities of the zygomaticus major and corrugator supercilii muscles to estimate spontaneous facial mimicry. Individual differences measures included trait emotional empathy (empathic concern) and the autism-spectrum quotient. We did not find that live performances enhanced the modulatory effect of trait differences on emotional contagion or spontaneous facial mimicry. However, we found that a high trait empathic concern was associated with stronger emotional contagion and corrugator mimicry. We found no two-way interaction between the autism spectrum quotient and emotional condition, suggesting that autistic traits did not modulate emotional contagion or spontaneous facial mimicry. Our findings imply that previous findings regarding the relationship between emotional empathy and emotional contagion/spontaneous facial mimicry using videos and photos could be generalized to real-life interactions.
Despite the fact that the linguistic outcomes of contact strongly depend on the structures of the languages involved, it is sociolinguistic factors that cause language contact to occur in the first place and to determinate its intensity and its direction (Thomason and Kaufman 1988). In particular, the sociolinguistic profile of the speech community in terms of linguistic repertoire, sociolinguistic norms and language use patterns play a significant role in shaping the outcomes of language contact. Decades of scholarly research in the fields of contact and historical linguistics have claimed that almost everything is possible in language contact and that constraints are easily violated by counterexamples. Yet, this does not mean that everything is equally likely to occur in any sociolinguistic setting (or “scenarios”, cf. Muysken 2010). Italian and German, or rather Italo-Romance and Upper German varieties spoken in Northern Italy (Rabanus et al. 2019), provide an excellent test bench to verify the impact of sociolinguistic factors in language contact. In fact, a large number of German varieties are spoken in Italy’s alpine regions where they have been in contact with Standard Italian and/ or Italo-Romance dialects for a long time (in some cases up to eight-nine centuries), differing from each other on many levels: status, official recognition, geographical continuity, access to Standard German, bi- multilingualism. Such differences are related to qualitative and quantitative variation of language contact phenomena in speech. Based on the outcomes of several research projects (cf. i.a. Dal Negro 2015 and Ciccolone and Dal Negro 2021) and on a large amount of conversational data documenting language use in a selection of sociolinguistically differentiated German-speaking speech communities in Northern Italy, the chapter focuses on instances of borrowing and explores comparatively their distribution in speech. The comparative analysis through all these speech communities is carried out taking into account quantitative factors such as the amount of borrowings in current speech, POS distribution, the relative weight of functional and lexical borrowings, types/tokens ratio of borrowed items and more general features such as directionality of borrowings, presence or absence of formal adaptation, variability of occurrence vs. fusion within the system.
This study examines zero marking, i.e. the absence of an overt exponent, in adjectival, nominal, and verbal inflectional morphology across languages. The first part of the study provides an overview of the distribution of zero markers in inflection paradigms using the UniMorph dataset. The results show that there is a general preference against zero marking. The distribution of zero markers varies to a great extent across languages and lemmas, the only robust trend being that they are avoided in cells that express a high number of grammatical values. The second part of this study examines the association between marker frequencies and phonological length, using the Universal Dependencies treebanks. While token frequency is a good predictor for the length of overt markers, it does not account for the occurrence of zero markers. This is taken as evidence to support a differential non-development scenario of zero marking rather than a phonetic reduction scenario.
Word identification accuracy is modulated by many factors including linguistic characteristics of words (frequent vs. infrequent), listening environment (noisy vs. quiet), and listener-related differences (older vs. younger). Nearly, all studies investigating these factors use high-familiarity words and noise signals that are either energetic maskers (e.g., white noise) or informational maskers composed of competing talkers (e.g., multitalker babble). Here, we expand on these findings by examining younger and older listeners' speech-in-noise perception for words varying in both frequency and familiarity within a simulated hospital noise that has important non-speech information. The method was inspired by the real-world challenges aging patients can face in understanding less familiar medical terminology used by healthcare professionals in noisy hospital environments. Word familiarity data from older and young adults were collected for 800 medically related terms. Familiarity ratings were highly correlated between the two age groups. Older adults' transcription accuracy for sentences with medical terminology that vary in their familiarity and frequency was assessed across four listening conditions: hospital noise, speech-shaped noise, amplitude-modulated speech-shaped noise, and quiet. Listeners were less accurate in noise conditions than in a quiet condition and were more impacted by hospital noise than either speech-shaped noise. Sentences with low-familiarity and low-frequency medical words combined with hospital noise were particularly detrimental for older adults compared to younger adults. The results impact our theoretical understanding of speech perception in noise and highlight real-world consequences of older adults' difficulties with speech-in-noise and specifically noise containing competing, non-speech information.
It is known that the norms of writing in any language are subject to changes under the influence of internal linguistic processes and external factors of influence. In this regard, the works aimed at studying the issues of linguistic norms, spelling, punctuation, regulation and consolidation of new linguistic phenomena identified in the context of modern realities, legalizing orthograms that have become familiar in the practice of writing, seem very relevant and promising. In accordance with the purpose of our research work, the article examines certain aspects of the issue of applying the rules and norms established by the rules of punctuation and spelling of the Kazakh language in modern writing practice, focuses on a number of rules that are often not taken into account when writing by writers, types of orthograms that introduce inconsistencies in the unity of word transmission, their relation to the norms of the language and the reasons for their use in practice. The research uses methods of collection, selection, systematization of linguistic material, as well as descriptive, statistical, comparative methods and the method of orthological analysis. The results of the study and the recommendations presented make a definite contribution to the unification of words with various variations in modern writing practice, additions and clarifications of spelling rules, and improvement of language literacy of students.
Proportions are one of the primary components of successful image composition during the visual art creation process, which, in turn, is determinant of the variety of effects of images on the viewer, including emotional reactions, attention, and aesthetic preference. The importance of image width and height ratio is especially visible in the current trend to adopt the widest possible screens in a variety of modern creative media applications: photo, video, computer games, etc. In the present study emotional and aesthetic evaluations of the three most popular aspect ratios that are used in digital media devices were compared. This was achieved by assessing emotional arousal and valence ratings together with the interest and appeal evaluations of realistic photos presented in 4:3, 16:9, and 21:9 aspect ratios. The results demonstrated that the widest images did not have an inherent advantage – photos presented in the mid-wide aspect ratio of 16:9 could be considered as more effective, because they were rated as evoking the most positive emotional reactions and as the most liked pictures. This demonstrated that single design features can have an independent emotional effect, which needs to be considered in visual design aiming to evoke emotional reactions to the viewer.
Abstract The literature are abound with studies on the impact of environmental, social, and governance (ESG) factors on a company‘s value, or more broadly, on its financial performance. However, most analyses concern developed markets, mainly because the largest rating agencies operate in these markets, as well as because these are markets where ESG awareness and regulations have developed much faster. In developing markets, the number of studies in this area is disproportionately smaller. Therefore, the purpose of this article is to examine the relationship between the environmental, social, and governance ratings (ESGR) of Polish listed companies included in the WIG-ESG index and their value. This study covered 36 companies listed in WIG-ESG in the period of 2019–2023. We used market data, financial data from examined companies and ESG data provided by Refinitive. The empirical results were negative but a non-statistically significant influence of ESGR and a company’s value. Further analysis indicated that none of the sub-ratings (environmental rating (ER), social rating (SR) and governance rating (GR)) had significant impact on value. The Polish market does not seem to recognize the potential of ESG factors in building the long-term value of companies and believes that the costs of ESG factors outweigh the benefits. Investors seem to disregard or underestimate ESG criteria when valuing companies, which may seem irrational when looking at the long-term effects of ESG factors. This article contributes to the existing literature by being part of the research on ESG factors and company value. The article expands the field of analysing the relationship between ESGRs and corporate value by examining this relationship not only using the overall ESGR, but also its individual sub-ratings. We also attempt to answer the question of where the channels of transmission of ESGRs on the value of the company are located, and which areas affect ratings. To the best of our knowledge, this is the first study of this type for the Polish market.
Music-evoked autobiographical memories (MEAMs) are typically elicited by music that listeners have heard before. While studies that have directly manipulated music familiarity show that familiar music evokes more MEAMs than music listeners have not heard before, music that is unfamiliar to the listener can also sporadically cue autobiographical memory. Here we examined whether music that sounds familiar even without previous exposure can produce spontaneous MEAMs. Cognitively healthy older adults (N = 75, ages 65–80 years) listened to music clips that were chosen by researchers to be either familiar or unfamiliar (i.e., varying by prior exposure). Participants then disclosed whether the clip elicited a MEAM and later provided self-reported familiarity ratings for each. Self-reported familiarity was positively associated with the occurrence of MEAMs in response to familiar, but not the unfamiliar, music. The likelihood of reporting MEAMs for music released during youth (i.e., the “reminiscence bump”) relative to young adulthood (20–25 years) included both music released during participants’ adolescence (14–18 years) and middle childhood (5–9 years) once self-reported familiarity was accounted for. These developmental effects could not be accounted for by music-evoked affect. Overall, our results suggest that the phenomenon of MEAMs hinges upon both perceptions of familiarity and prior exposure.
Automatically detecting mental state such as stress from video images of the face could support evaluating stress responses in applicants for high risk jobs or contribute to timely stress detection in challenging operational settings (e.g., aircrew, command center operators). Challenges in automatically estimating mental state include the generalization of models across contexts and across participants. We here aim to create robust models by training them using data from different contexts and including physiological features. Fifty-one participants were exposed to different types of stressors (cognitive, social evaluative and startle) and baseline variants of the stressors. Video, electrocardiogram (ECG), electrodermal activity (EDA) and self-reports (arousal and valence) were recorded. Logistic regression models aimed to classify between high and low arousal and valence across participants, where "high" and "low" were defined relative to the center of the rating scale. Accuracy scores of different models were evaluated: models trained and tested within a specific context (either a baseline or stressor variant of a task), intermediate context (baseline and stressor variant of a task), or general context (all conditions together). Furthermore, for these different model variants, only the video data was included, only the physiological data, or both video and physiological data. We found that all (video, physiological and video-physio) models could successfully distinguish between high- and low-rated arousal and valence, though performance tended to be better for (1) arousal than valence, (2) specific context than intermediate and general contexts, (3) video-physio data than video or physiological data alone. Automatic feature selection resulted in inclusion of 3-20 features, where the models based on video-physio data usually included features from video, ECG and EDA. Still, performance of video-only models approached the performance of video-physio models. Arousal and valence ratings by three experienced human observers scores based on part of the video data did not match with self-reports. In sum, we showed that it is possible to automatically monitor arousal and valence even in relatively general contexts and better than humans can (in the given circumstances), and that non-contact video images of faces capture an important part of the information, which has practical advantages.
Abstract The Holistic Hypothesis asserts that formulaic expressions (FEs) are processed more rapidly than non-formulaic expressions (non-FE items) by both native speakers (NSs) and L2 learners of English. This study utilized an acceptability judgment task and a self-paced reading task to investigate the online processing of FEs and non-FE items among bilingual speakers (L1 English, L2 Chinese) in both contextual and non-contextual conditions. Meanwhile, a familiarity rating task was employed to measure whether there is a familiarity effect in item processing. The results consistently provided support for the Holistic Hypothesis, indicating that learners of Chinese at each level exhibited faster processing of FEs compared to non-FE items, regardless of the presence or absence of context. However, the influence of item familiarity, rather than the proficiency effect, contributed to the improvement of L2 learners’ eventual processing abilities. Distinct patterns also emerged when comparing data from NSs and L2 learners of Chinese, highlighting L2 learners’ more pronounced processing advantage, characterized by faster response times (RTs) to FEs compared to non-FE items. Through an analysis of Chinese L2 data, this study sheds light on the interplay between the usage based approach and chunking within the cognitive approach to L2 learning.
The human mind automatically divides continuous experience into meaningful events (event segmentation). Despite abundant evidence that some kinds of situation changes (e.g., action, goal, or location changes) contribute to event segmentation, a component of experience that is critical for understanding and predicting others’ behavior, emotion, is rarely investigated. In two experiments, we sought to establish that viewers can track emotion changes while viewing naturalistic videos, and that these changes contribute to event segmentation. Participants watched commercial film excerpts while identifying either emotion changes or event boundaries (moments that separate two events) of different grains (Experiment 1: neutral-grain; Experiment 2: fine-grain or coarse-grain). We found that participants agreed with each other about when emotion changes occurred in the videos, demonstrating that viewers are able to track changes in the emotional content of dynamic naturalistic videos as they are experienced. Moreover, the emotion changes participants identified were temporally aligned with the event boundaries identified by other groups. In addition, valence and arousal ratings from separate groups of participants uniquely predicted the likelihood of identifying emotion changes and event boundaries, even after accounting for other types of change. However, emotion changes were more strongly tied to valence changes than arousal changes while coarse boundaries were more strongly associated with affective changes than were fine boundaries. These novel findings suggest that emotional information plays a substantial role in structuring ongoing experiences into meaningful events, providing a stronger basis for understanding how emotion shapes the perception and memory of everyday experiences.
BACKGROUND AND OBJECTIVES: The conditioned-intrusion paradigm was designed to provide insight into the relationship between fear conditioning and intrusive memory formation, which is relevant to understanding posttraumatic stress disorder symptoms and treatment. However, boundary conditions of this new paradigm have not been explored and it is currently not known whether findings from this work are valid in a clinical context. METHODS: In the current study, we explored the relationship between stress reactivity to trauma film clips, usual exposure to violent media, renewal of fear conditioning using skin conductance as well as subjective ratings, and the effect of shock versus film clip during conditioning on the frequency of intrusive memories. An adapted fear conditioning paradigm using trauma clips as unconditional stimuli was used, and participants subsequently reported intrusive memories of the trauma clips. RESULTS: Skin conductance responses to conditioned stimuli paired with shocks and film clips were significantly higher than conditioned stimuli paired with film clips alone. Subjective stress reactivity, previous exposure to violent media, and film valence rating were associated with the frequency of intrusive memories. No aspects of fear conditioning were associated with intrusive memories, and factor analysis suggested the fear conditioning and stress related to film clip viewing were mostly separate constructs. Similarly, content and triggers of intrusive memories were usually film-clip related rather than conditional stimulus related. LIMITATIONS: We did not observe strong conditioning effects of the unconditional stimuli to conditional stimuli, which were shapes rather than high frequency stimuli such as faces. CONCLUSIONS: These findings provide potential boundary conditions for this paradigm and suggest multiple ways in which the validity of the paradigm can be tested in the future.
Introduction: Sleep loss is common during the perinatal period; however, few studies have assessed potential consequences of insufficient sleep for postnatal emotional responding, a key contributor to parenting behaviors with implications for parent-infant bonding and mental health. To generate hypotheses for future work assessing perinatal sleep and emotion-related outcomes, this pilot study explored whether prenatal sleep duration predicted postnatal emotional responding in a sample at risk for postpartum depression. Methods: Participants were nine birthing parents with a prior mood disorder who were not in a current episode at enrollment. We estimated sleep with actigraphy collected for 1 week at 33 weeks' gestation and at 2 and 6 weeks postpartum. Following each week, participants completed an emotional evaluation task, rating the valence and arousal of standardized images from the International Affective Picture System. We tested whether average prenatal (33 weeks) nighttime sleep duration predicted concurrent and future responsiveness to emotional images, quantified by participants' reaction times and arousal/valence ratings. Results: s ≤.043). Conclusions: In this small sample of birthing parents at risk for postpartum depression, shorter prenatal sleep duration predicted faster reactions to emotional stimuli and blunted arousal responses to negative images. Although preliminary, these findings justify further study of the role of prenatal sleep in postpartum emotional responses and how these factors may impact parent-infant outcomes.
Abstract The epilogue rearranges the verse covered in the book as a whole back into a chronological narrative, from 1150 to 1500, to balance the non-chronological treatment of the topic necessary in the book as a whole. The time around 1400 is picked out as perhaps the hinge or pivot of the whole history of English poetry, the moment of the greatest potential and variety. The chapter reviews and emphasizes the uncentredness and possibility of early poetry: in its distribution, whether in writing or performance; in its lack of strong linguistic norms; and in the absence of a dominant prestige form. The task of reading early poetry is passed on to the book’s readers.
Previous research has variably indicated the role of working memory in error detection by which working memory played a role in rhythmic error detection but not melodic error detection. Here, we devised a longer melodic error detection task for college musicians in an auditory, rather than visual, condition using classical excerpts, which we compared to briefer visual and auditory control conditions. These tests were compared to performance on a test of verbal working memory (forward digit span test) and an experimenter-created tonal working memory test. The tonal working memory test was positively related to the forward digit span test, the melodic error detection, and the visual control but not to the auditory control. Performance on the error detection test was not significantly related to year in school, level of aural skills class, years of private piano, or level of group piano class. Our participants performed similarly on the aurally presented melodic error detection of classical excerpts and the briefer visual control but not on the briefer aural control. Among other variables, years of experience on a second instrument was a significant predictor of error detection skill. High familiarity ratings with a classical excerpt did not yield a relationship to error detection performance.