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Bidirectional Encoder Representations from Transformers (BERT), a revolutionary model in natural language processing (NLP), has significantly impacted text-related tasks including text classification. Several BERT models were developed for Arabic language. While many studies have compared their overall performance for text classification tasks, none has dug deeper and investigated the relationship between their pretraining data and their performance. This study investigates this relationship by utilizing ten models and evaluating them on eight diverse classification tasks using metrics such as accuracy and F1 score. Results revealed variations in performance across tasks which was mainly due to the models pretraining corpora. The study emphasizes the impact of pretraining data size, quality, and diversity on model adaptability. Models pretrained on specific corpora, despite larger sizes, may not outperform those pretrained on more diverse datasets. Notably, domain-specific tasks, such as medical and poetry classification, unveiled performance gaps compared to the original English BERT. The findings suggest the necessity of reevaluating the pretraining approach for Arabic BERT models. Balancing quantity and quality in pretraining corpora, spanning various domains, is identified as crucial. The study provides insights into optimizing pretraining strategies for enhanced performance and adaptability of Arabic BERT models in diverse text classification tasks, offering valuable guidance for researchers and practitioners in the field of NLP. [ABSTRACT FROM AUTHOR]

The revised hierarchical model was proposed in 1994 (Kroll & Stewart, 1994) to explain how 2 languages are represented in the mind of late language learners. The model proposed dynamic asymmetric relations between the 2 languages with an underlying conceptual system as a means of addressing issues current at the time regarding lexical retrieval in picture and word naming as well as translation across languages. The broader insights from that model remain relevant today and continue to guide research in bilingual language processing. Three such insights—the role of context, the relation between the 2 languages, and the importance of task details—are described. [ABSTRACT FROM AUTHOR]

This article analyses the linguistic landscape (LL) of tourism in Tanzania, specifically in Arusha Kilimanjaro, and Manyara regions. It seeks to determine language representation, the key actors, and power dynamics between the languages represented in the LL. It collected 258 signs in seven tourist sites in these regions in the Northern Safari Circuit of Tanzania in February and March 2024 using a digital camera. It analysed the data grounded in Kress and van Leeuwen’s (2006) framework for analysing visual signs. Findings indicate that English monolingual signs are predominant, followed by English and Kiswahili bilingual signs, and finally, Kiswahili monolingual signs. No ethnic community languages (ECLs) are represented on the signs in the studied LL. The data showed that top–down actors favour both English and Kiswahili for profit and pride, whereas bottom–up actors favour only English for profit. English is dominant in both top–down and bottom–up signage, whereas ECLs are conspicuously absent in the LL of tourism sites, implying the need for (i) policy intervention to enhance their presence in the public space and (ii) diversification of tourism marketing strategies to incorporate aspects of ECLs and cultures to attract tourists seeking authentic, varied experiences.

The detection of fake news has emerged as a crucial area of research due to its potential impact on society. In this study, we propose a robust methodology for identifying fake news by leveraging diverse aspects of language representation and incorporating auxiliary information. Our approach is based on the utilisation of Bidirectional Encoder Representations from Transformers (BERT) to capture contextualised semantic knowledge. Additionally, we employ a multichannel Convolutional Neural Network (mCNN) integrated with stacked Bidirectional Gated Recurrent Units (sBiGRU) to jointly learn multi-aspect language representations. This enables our model to effectively identify valuable clues from news content while simultaneously incorporating content- and context-based cues, such as user posting behaviour, to enhance the detection of fake news. Through extensive experimentation on four widely used real-world datasets, our proposed framework demonstrates superior performance (↑3.59% (PolitiFact), ↑6.8% (GossipCop), ↑2.96% (FA-KES), and ↑12.51% (LIAR), considering both content-based features and additional auxiliary information) compared to existing state-of-the-art approaches, establishing its effectiveness in the challenging task of fake news detection. [ABSTRACT FROM AUTHOR]

Affective tasks, including sentiment analysis, emotion classification, and sarcasm detection have drawn a lot of attention in recent years due to a broad range of useful applications in various domains. The main goal of affect detection tasks is to recognize states such as mood, sentiment, and emotions from textual data (e.g., news articles or product reviews). Despite the importance of utilizing preprocessing steps in different stages (i.e., word representation learning and building a classification model) of affect detection tasks, this topic has not been studied well. To that end, we explore whether applying various preprocessing methods (stemming, lemmatization, stopword removal, punctuation removal and so on) and their combinations in different stages of the affect detection pipeline can improve the model performance. The are many preprocessing approaches that can be utilized in affect detection tasks. However, their influence on the final performance depends on the type of preprocessing and the stages that they are applied. Moreover, the preprocessing impacts vary across different affective tasks. Our analysis provides thorough insights into how preprocessing steps can be applied in building an effect detection pipeline and their respective influence on performance. [ABSTRACT FROM AUTHOR]

To forecast the sociolinguistic dynamics of the language, to determine the level of its vitality and to provide adequate measures of language policy and planning, it seems important to analyze the structures of the symbolic components of the language situation, which include language representations and language attitudes, that is, social attitudes towards language. The article presents the results of the analysis of the main types of Tatar language representations and linguistic attitudes among speakers of the Mishar idiom of the Tatar language. The data were collected in the regions where the Mishary Tatars live, namely in the Middle Volga region and in Prisurie. The main research method was a semi-structured interview with subsequent analysis of the obtained data, its classification and interpretation. The paper proposes five clusters of language representations in the minority situation: representations related to the instrumental, symbolic and regulative functions of language, on the one hand, and representations related to the actualized identity structures and to the deontic attitudes of the individual, on the other. In connection with these classes of representations and taking into account language forms, language competences and language practices, a typology of language loyalty is proposed, which includes instrumental loyalty, symbolic loyalty, loyalty according to the forms of language used, loyalty according to language competences and prescriptive loyalty. The material analysis showed the prevalence of positive representations of the Mishar idiom among its speakers, the presence of active positive loyalty in oral spheres of communication at the local level, a high level of idiom preservation, and the integrative nature of sociolinguistic dynamics. At the same time, the situation should be regarded as diglossic both in relation to the Russian language and to the literary Tatar language, which is considered to be prestigious.

The article deals with the language representation as a multifaceted format of interpretive knowledge, as a projection of the individual-author worldview, as a synergy of the writer’s intentions, his idiostyle, and the parameters of the cognitive-plot matrix of the text. Attention is drawn to the both relationship and interdependence of the both language representations and concepts as formats of knowledge, including as formats of literary knowledge. The role of language representations in text literary architectonics is analysed in detail. The presence of dominant language representation in the architectonics of literary text is determined. The fact that the model “The Harsh North” appears as a dominant language representation in the architectonics of the research text is determined. The specific features of the formation of the nominative field of the dominant text language representation of “The Harsh North” are revealed. The prevalence of multi-component nominees in the nominative field of the dominant text representation of “The Harsh North” is determined. The conjugation of the nominative fields of three literary concepts, such as the literary concept of “nature”, the literary concept of “space”, the literary concept of “time” which contributes to the creation of a holistic taxonomic model “The Harsh North” in J. London’s “The Call of the Wild” is revealed.

This study analyses variation and change in Uruguayan Spanish address between formal (usted) and informal variants (tú, vos). It focusses on address representations in children's literature written between 1918 and 1973 – foundational texts that helped consolidate national identity. Our study answers the following questions: (a) What were the most frequent pronominal and verbal address forms employed in early Uruguayan children's literature? (b) What were their pragmatic and stylistic contexts of use? And (c) To what extent did those forms and uses differ from their contemporary counterparts? The second-person pronouns and verbs from eleven children's books were analysed quantitatively to establish frequencies. We found that early children's literature presented usted and tú as the urban norm. Vernacular vos was practically absent until the 1940s, and afterwards it was found only in specific constrained contexts. This differs markedly from contemporary literature for children, which favours voseo and reflects orality quite accurately. [ABSTRACT FROM AUTHOR]

The detection of fake news has emerged as a crucial area of research due to its potential impact on society. In this study, we propose a robust methodology for identifying fake news by leveraging diverse aspects of language representation and incorporating auxiliary information. Our approach is based on the utilisation of Bidirectional Encoder Representations from Transformers (BERT) to capture contextualised semantic knowledge. Additionally, we employ a multichannel Convolutional Neural Network (mCNN) integrated with stacked Bidirectional Gated Recurrent Units (sBiGRU) to jointly learn multi-aspect language representations. This enables our model to effectively identify valuable clues from news content while simultaneously incorporating content- and context-based cues, such as user posting behaviour, to enhance the detection of fake news. Through extensive experimentation on four widely used real-world datasets, our proposed framework demonstrates superior performance (↑3.59% (PolitiFact), ↑6.8% (GossipCop), ↑2.96% (FA-KES), and ↑12.51% (LIAR), considering both content-based features and additional auxiliary information) compared to existing state-of-the-art approaches, establishing its effectiveness in the challenging task of fake news detection.

This contribution proposes a reflection on the representation of languages in Riad Sattouf’s autobiographical comic book The Arab of the Future. The childhood languages that are drawn in the book are not always faithful to the childhood spoken languages. This staging of the language’s unfamiliarity or familiarity makes visible questions of cultural or linguistic transmission (Arabic, French) and language ideologies within the family, at school or in wider society, both in France and Syria. Although Arabic is progressively being forgotten by the character-narrator, his childhood plurilingualism lasts in a form of linguistic overconsciousness, which captures many linguistic objects with comic art tools.

The paper is dedicated to the analysis of irregular intensifying constructions in Fyodor Dostoevskys individual style, more specifically of irregular lexical combinations including an intensifier and a main word. The meaning of intensifies is completely focused on expressing the intensity of an attribute, action or state denominated by the main word. Fyodor Dostoevskys writing style tends to form certain types of irregular lexical combinations including intensifiers. Through a case study of intensifiers ochen , goryachii / goryacho , izo vsekh sil , etc. the article describes several main types of irregular combinations with the view to find out semantic effects of irregular combinability. The analysis has covered the complete corpus of Fyodor Doestoevskys texts (fiction, journalism, private correspondence, business correspondence and documents). The first discriminant mark of irregular combinations is the semantic contradiction between the terms, the violation of idiomatic compatibility rules is the second feature taken into account. Whereas collocational rules in modern Russian differ a lot from the language norms of the 19th century, the subcorpus of 19th century texts of the National Russian Corpus serves to test the irregular idiomatic combinability. The article shows how the irregular combinability causes context meaning shifts profiling peripheral semantic features of the main word or imposing on it an untypical and contradictory semantics. In irregular lexical combinations, the language representation changes due to the original authors reinterpretation of the referential situation. The irregular lexical combinations with intensifiers are thereafter a distinctive feature of Fyodor Dostoevskys individual writing style that reveals his original conceptualization of the world.

In natural language processing, most text representation methods can be generally categorized into two paradigms: static and dynamic. Both have distinctive advantages, which are reflected in the cost of training resources, the scale of input data, and the interpretability of the representation model. Dynamic representation methods, such as BERT, have achieved excellent results on many tasks based on expensive pre-training. However, this representation paradigm is black-box, and the intrinsic properties cannot be measured by standard word similarity and analogy benchmarks. Most importantly, it is not in all cases that there are adequate resources and unlimited data to use. While static methods are solid alternatives for these scenarios because they can be efficiently trained with limited resources, keeping straightforward interpretability and verifiable intrinsic properties. Although many static embedding methods have been proposed, few attempts have been made to investigate the connections between these algorithms. Thus, it is natural to ask which implementation is more efficient, and is there any way to combine the merits of these algorithms into a generalized framework? In this paper, we try to explore answers to these questions by focusing on two popular static embedding models, Continual-Bag-of-Words (CBOW) and Skip-gram (SG), with detailed analysis of their merits and drawbacks under both Negative Sampling (NS) and Hierarchy Softmax (HS) settings. Then, we propose a novel learning framework to train generalized static embeddings in a unified architecture. Our proposed method is estimator-agnostic. Thus, it can be optimized by either NS, HS, or any other equivalent estimators. Experiments show that embeddings learned from the proposed framework outperform strong baselines on standard intrinsic evaluations. We also test the proposed method on three extrinsic tasks. Empirical results show that the proposed method achieves considerable improvements across all these tasks. [ABSTRACT FROM AUTHOR]

Статья посвящена анализу языковой репрезентации ментальных представлений о подобии человека и технических устройств. В данной работе исследуются образные переосмысления, выявляющие антропоцентрическую сущность механизмов в исторической динамике. Материал исследования составили существительные русского языка, обозначающие различные приспособления, от самых примитивных, изобретенных в древности, до сложных агрегатов наших дней. Проанализировано множество примеров их употребления в словарях, произведениях русских писателей, в материалах публицистического характера, а также в Национальном корпусе русского языка.

Understanding human language is one of the key themes of artificial intelligence. For language representation, the capacity of effectively modeling the linguistic knowledge from the detail-riddled and lengthy texts and getting ride of the noises is essential to improve its performance. Traditional attentive models attend to all words without explicit constraint, which results in inaccurate concentration on some dispensable words. In this work, we propose using syntax to guide the text modeling by incorporating explicit syntactic constraints into attention mechanisms for better linguistically motivated word representations. In detail, for self-attention network (SAN) sponsored Transformer-based encoder, we introduce syntactic dependency of interest (SDOI) design into the SAN to form an DOI SAN with syntax-guided self-attention. Syntax-guided network (SG-Net) is then composed of this extra SDOI-SAN and the SAN from the original Transformer encoder through a dual contextual architecture for better linguistics inspired representation. The proposed SG-Net is applied to typical Transformer encoders. Extensive experiments on popular benchmark tasks, including machine reading comprehension, natural language inference, and neural machine translation show the effectiveness of the proposed SG-Net design. [ABSTRACT FROM AUTHOR]

Bidirectional Encoder Representations from Transformers (BERT) has gained increasing attention from researchers and practitioners as it has proven to be an invaluable technique in natural languages processing. This is mainly due to its unique features, including its ability to predict words conditioned on both the left and the right context, and its ability to be pretrained using the plain text corpus that is enormously available on the web. As BERT gained more interest, more BERT models were introduced to support different languages, including Arabic. The current state of knowledge and practice in applying BERT models to Arabic text classification is limited. In an attempt to begin remedying this gap, this review synthesizes the different Arabic BERT models that have been applied to text classification. It investigates the differences between them and compares their performance. It also examines how effective they are compared to the original English BERT models. It concludes by offering insight into aspects that need further improvements and future work. [ABSTRACT FROM AUTHOR]

The article deals with topical issues of building an individual author’s picture based on the material of color-lexemes in the poetic discourse of Arthur Rimbaud. Poetic discourse is understood as a synthesis of various language forms specific to the author’s style, which form a communication system that represents information about the author’s alternative world, reflected in the poetic text, endowed with pragmatic content, represented by an individual set of language tools characteristic of this author. Coloronyms that represent evaluative and emotional personal meanings that have a certain impact potential are among the most frequent and special-meaning language tools of Artur Rimbaud’s individual author’s poetic style. The specificity of language representations of the individual author’s worldview in poetic discourse, which takes an active part in the formation of a dynamic worldview and determines the effect of an anthropogenic factor as a result of individual speech activity, is due to one of the main components of the poetic discourse represented by the author’s linguistic personality. It directly depends on his individual abilities and characteristics, creative techniques that underlie the created literary works. This approach considers the author of a literary text as a subject endowed with a specific set of individual traits, which allows us to reveal the language personality of the poet, which gets its expression in the work, its impact on the reader’s personality, along with other aspects of poetic discourse.

Family dogs are exposed to a continuous flow of human speech throughout their lives. However, the extent of their abilities in speech perception is unknown. Here, we used functional magnetic resonance imaging (fMRI) to test speech detection and language representation in the dog brain. Dogs (n = 18) listened to natural speech and scrambled speech in a familiar and an unfamiliar language. Speech scrambling distorts auditory regularities specific to speech and to a given language, but keeps spectral voice cues intact. We hypothesized that if dogs can extract auditory regularities of speech, and of a familiar language, then there will be distinct patterns of brain activity for natural speech vs. scrambled speech, and also for familiar vs. unfamiliar language. Using multivoxel pattern analysis (MVPA) we found that bilateral auditory cortical regions represented natural speech and scrambled speech differently; with a better classifier performance in longer-headed dogs in a right auditory region. This neural capacity for speech detection was not based on preferential processing for speech but rather on sensitivity to sound naturalness. Furthermore, in case of natural speech, distinct activity patterns were found for the two languages in the secondary auditory cortex and in the precruciate gyrus; with a greater difference in responses to the familiar and unfamiliar languages in older dogs, indicating a role for the amount of language exposure. No regions represented differently the scrambled versions of the two languages, suggesting that the activity difference between languages in natural speech reflected sensitivity to language-specific regularities rather than to spectral voice cues. These findings suggest that separate cortical regions support speech naturalness detection and language representation in the dog brain.

The present study focuses on the impact of graphic symbols used in Augmentative and Alternative Communication (AAC) on clause construction. It is not yet well-understood to what extent communication produced via graphic symbols differs from verbal production. This study attempts shed light on the impact of the graphic symbol modality on message construction beyond individual differences, language knowledge, and language-specific patterns by providing a direct comparison between children's verbal and graphic symbol production. Nineteen typically developing Hebrew-speaking children aged 4–5 years were presented with 16 short videos of actions and were asked to express what they saw verbally and by choosing among graphic symbols displayed on an iPad communication board. The 570 clauses produced by the children were coded and analyzed. A significant difference was found in favor of verbal speech across different syntactic structures in terms of utilization of the target lexicon, syntactic complexity, and expected target word order. These results are consistent with the existing literature for English. Implications for AAC practices are discussed, highlighting the notion that using graphic symbols to represent spoken language may not reflect actual linguistic knowledge and that adequate, explicit instruction is necessary for graphic representation of more complex linguistic structures. [ABSTRACT FROM AUTHOR]

Copyright of Lublin Studies in Modern Languages & Literature / Lubelskie Materialy Neofilologiczne is the property of Maria Curie-Sklodowska University, Department of German & Applied Linguistics and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

• Propose to use Transformers to encode the complex semantics from video clips. • Experimentally demonstrate outstanding improvements compared with previous methods. • Show differences of Transformer variants in video QA tasks. With the goal of correctly answering questions about images or videos, visual question answering (VQA) has quickly developed in recent years. However, current VQA systems mainly focus on answering questions about a single image and face many challenges in answering video-based questions. VQA in video not only has to understand the evolution between video frames but also requires a certain understanding of corresponding subtitles. In this paper, we propose a language Transformer-based video question answering model to encode the complex semantics from video clips. Different from previous models which represent visual features by recurrent neural networks, our model encodes visual concept sequences with a pre-trained language Transformer. We investigate the performance of our model using four language Transformers over two different datasets. The results demonstrate outstanding improvements compared to previous work. [ABSTRACT FROM AUTHOR]

Westergaard's microcue account raises the question of the exact nature of language transfer in the acquisition of languages as well of how L1/Ln input interacts with the principles of universal grammar (UG) during processing. In order to consider in more detail the actual representation building, processing mechanisms that would be involved, her approach will be spelled out in terms of the Modular Cognition Framework (see Sharwood Smith, 2017; Sharwood Smith and Truscott, 2014; Truscott and Sharwood Smith, 2004, 2019). As well as identifying the way in which microcues would be constructed, this analysis in particular will have the effect of undermining the concept underlying the transfer metaphor as a way of characterizing crosslinguistic influence. [ABSTRACT FROM AUTHOR]

This paper presents an analytical review of scientific works devoted to one of the topical studies in cognitive and cultural linguistics, namely, to the concept of "money", which is included in the corpus of basic concepts of European civilization. Concepts as complex mental formations attract special attention of scientists studying the problem of language conceptualization of the person’s environmental world. Language units of different levels are studied in their correlation with the cognitive structure of the concept knowledge. The framework consists of systematization of the majority of existing scientific results of verbal representation, structuring of the concept of "money" in the context of Russian, English, German, and French. A comparative analysis of the ways and means of language representation of the concept "money" in Russian, English, German, and French sets the combination of versatile and specific features that embody the nature of the concept of "money" in these national languages. The obtained scientific findings represent the opportunities of embodiment of general cultural concept of "money" in national linguocultures. The practical value is determined by the fact that the obtained structured scientific data in the specified conceptual field can be used by scientists when developing linguoculturological dictionaries of basic concepts of European culture, as well as in the development of training courses with the dictionaries in question as content database.

Xiaolu Guo's A Concise Chinese-English Dictionary for Lovers is a novel in which language has a special protagonism. The main character, Z, is a Chinese girl who goes to London to improve her basic English. Her idiolect is thus characterised by a great quantity of linguistic errors of different types. This lack of proficiency in English makes cross-cultural communication really difficult. Therefore, language becomes in this novel not only a characterisation tool, but also an essential aspect of the plot. Moreover, it is also a paramount source of humour, since there is plenty of jokes based, for instance, on puns, many of which derive from Z's lack of linguistic competence. The main objective of this paper is to analyse language representation in the source text as well as in the Spanish, Italian and French versions of the novel from the perspective of relevance theory. Out of the three versions, the Spanish one reflects the highest interpretive resemblance in this regard, whereas the Italian one occupies the opposite pole of the scale. With regard to the translation of wordplay, the pragmatic scenario is normally maintained in the TT, although there are statistically significant differences between the three versions and across different types of puns. [ABSTRACT FROM AUTHOR]

Bidirectional Encoder Representations from Transformers (BERT) has gained increasing attention from researchers and practitioners as it has proven to be an invaluable technique in natural languages processing. This is mainly due to its unique features, including its ability to predict words conditioned on both the left and the right context, and its ability to be pretrained using the plain text corpus that is enormously available on the web. As BERT gained more interest, more BERT models were introduced to support different languages, including Arabic. The current state of knowledge and practice in applying BERT models to Arabic text classification is limited. In an attempt to begin remedying this gap, this review synthesizes the different Arabic BERT models that have been applied to text classification. It investigates the differences between them and compares their performance. It also examines how effective they are compared to the original English BERT models. It concludes by offering insight into aspects that need further improvements and future work.

Introduction. The changing reality of libraries actually is a form of communication by the library management. The Language of libraries, is a representation of libraries through language. Various definitions of libraries from the literatures are representations of libraries through language. This study aims to examine the changing meaning of libraries from time to time. Data Collection Method. Data collection was conducted by involving documentation of various discourses discussing libraries. Analysis Data. Discursive genealogy was used to analyse the data to provide changes of meaning of libraries from time to time. Results and Discussions. The result showed that the meaning of libraries continues to change. The current meaning of libraries is a room or institution where information is stored and gathered. Libraries are hubs of users' needs including space, services, and various resources to support education, research, information, and recreation. Conclusion. Various changes of meaning of Libraries from time to time show that the representation of libraries through language has changed. The meaning of libraries may change and deconstruct.

The article analyzes basic approaches to defining the notion “ideologeme” and its role in contemporary media discourse. The study focuses on such linguistic forms of expression the meaning which eventually turn into the representation of ideology by language means – ideologeme. The article gives not only a review of ideologeme classifications which have been applied in Russian science, but also represents a range of ideologemes recently detected in media texts of Spain and the UK.

Рассматриваются когнитивные основания ментального феномена воображения и языковая репрезентация способности создания и формирования образа. Анализ языковой концептуализации воображения опирается на метод когнитивного моделирования ситуации. Эмпирический материал свидетельствует о том, что ситуация воображения может быть категоризована глаголами, которые по-разному ее характеризуют. Обобщение компонентов семантической структуры языковых выражений и контекстов их репрезентации позволило построить когнитивную модель ситуации воображения, участниками которой будут являться субъект воображения, процесс воображения как создание мысленных образов в определенной пространственно-временной среде и объект воображения (воображаемое).

Linguistic diversity has become a defining feature of schools in the twenty-first century. How do children make sense of such diversity and their own linguistic identities? This article draws on data generated through a multi-site inquiry with five English and French schools in Canada and France to investigate children's plurilingualism. According to educational policy and curriculum in each context, all of the children involved in this study were receiving instruction at school in English and French. In addition, many children spoke other languages outside of school, at home and in their communities. At the conclusion of each 4–6 month research collaboration in each school, children engaged in making collages that responded to the question, 'How does it look and feel to be plurilingual'? Drawing on social theories of language representation and plurilingualism, the focus herein is on analyzing how children's representations of plurilingualism made visible through the medium of collage. This article argues for the usefulness of creative multimodal arts-based methods in applied linguistics research and in particular for engaging plurilingual children as co- investigators. [ABSTRACT FROM AUTHOR]

Measuring functional coupling in complex systems is an important task for good design practice, though historically it has been an art of subjective judgement. With the recent advancements in Deep Learning and Natural Language Processing, functional requirements (FRs) and design parameters (DPs), which are expressed as words and sentences, can be represented in a vector space. The sentence embedding model, BERT, was used in this paper to vectorize FRs and DPs, to calculate functional independence and to study how metrics for functional coupling measurement can be enhanced. It was found that semantic similarity among FRs and DPs, represented in vector space, could be used to compute quantitative values for metrics of functional independence. It was also found that design cases where coupling was unambiguous yielded the best results, while cases where laws of physics needed to define the FR-DP relationship did not transliterate well to the natural language used to express the FR-DP highlighted the limitations of the model in its current state. This study, however, demonstrates a great opportunity to develop a robust, fine-tuned design language representation model for accurately measuring functional independence as a part of our effort to enhance design intelligence. [ABSTRACT FROM AUTHOR]

This study aims to investigate L2-to-L1 cross-linguistic influence on bilinguals’ representation and processing with three psycholinguistics tasks. The interest in this type of effect lies in its possible association with cognitive control development. Our study focuses on possible influences of the non-dominant language on the dominant language: we analyzed whether highly proficient Brazilian Portuguese-English late bilinguals immersed in the L1 context behaved differently from Brazilian Portuguese monolinguals in regards to sentences in the L1 that simulated an L2-specific construction (true resultative). We conducted a maze task in order to analyze the speakers’ linguistic processing and a speeded acceptability judgment task in order to analyze their linguistic representation. We also observed participants’ behavior towards a construction available in both languages (depictive). The overall results indicate that bilinguals processed both constructions faster than monolinguals, but the difference between the groups was significantly larger towards the true resultative construction. However, there was no significant difference between the groups in relation to how they perceived the acceptability of both constructions. We interpret the results as evidence that the L2 influence on the L1 occurs during real time sentence processing, but it does not result in changes in the overall L1 representation.

The study reports the results of a sociolinguistic survey on the variety of Kabylian spoken in the regions of Kabylia Maritime or what is commonly called "The Sahel". Then we aim to analyze the phenomenon of linguistic insecurity through the study of linguistic representations, its various manifestations among tasahlit speakers.

This paper presents an analytical review of scientific works devoted to one of the topical studies in cognitive and cultural linguistics, to the concept of "money" that is included in the corpus of basic concepts of European civilization. The framework consists of systematization of most of existing scientific results of verbal representation, structuring of the concept of "money" in the context of Russian, English, German, French languages. A comparative analysis of the ways and means of language representation of the concept "money" in Russian, English, German, French, sets the combination of versatile and specific features that embody the nature of the concept of "money" in these national languages. The obtained scientific findings represent the opportunities of an embodiment of the general cultural concept of "money" in national linguocultures. The practical value is determined by the fact that the obtained structured scientific data in the specified conceptual field can be used by scientists when developing linguoculturological dictionaries of basic concepts of European culture, as well as in the development of training courses, for which these dictionaries will become a content database. [ABSTRACT FROM AUTHOR]

Experiments examining identity priming from attended and ignored novel words (words that are used only once except when repetition is required due to experimental manipulation) in a lexical decision task are reported. Experiment 1 tested English monolinguals whereas Experiment 2 tested Twi (a native language of Ghana, Africa)-English bilinguals. Participants were presented with sequential pairs of stimuli composed of a prime followed by a probe, with each containing two items. The participants were required to name the target word in the prime display, and to make a lexical decision to the target item in the probe display. On attended repetition (AR) trials the probe target item was identical to the target word on the preceding attentional display. On ignored repetition (IR) trials the probe target item was the same as the distractor word in the preceding attentional display. The experiments produced facilitated (positive) priming in the AR trials and delayed (negative) priming in the IR trials. Significantly, the positive and negative priming effects also replicated across both monolingual and bilingual groups of participants, despite the fact that the bilinguals were responding to the task in their non-dominant language. [ABSTRACT FROM AUTHOR]

Copyright of Synergies France is the property of GERFLINT (Groupe d'Etudes et de Recherches pour le Francais Langue Internationale) and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)