Language Features Research Articles

Improving visual grounding with multi-modal interaction and auto-regressive vertex generation

We propose a concise and consistent network focusing on multi-task learning of Referring Expression Comprehension (REC) and Segmentation (RES) within Visual grounding (VG). To simplify the model architecture and achieve parameter sharing, we reconstruct the Visual grounding task as a floating-point coordinate generation problem based on both image and text inputs. Consequently, rather than separately predicting bounding boxes and pixel-level segmentation masks, we represent them uniformly as a sequence of coordinate tokens and output two corner points of bounding boxes and polygon vertices autoregressively. To improve the accuracy of point generation, we introduce a regression-based decoder. Inspired by bilinear interpolation, this decoder can directly predict precise floating-point coordinates, thus avoiding quantization errors. Additionally, we devise a Multi-Modal Interaction Fusion (M2IF) to address the imbalance between visual and language features in the model. This module focuses visual information on regions relevant to textual descriptions while suppressing the influence of irrelevant areas. Based on our model, Visual grounding is realized through a unified network structure. Experiments conducted on five benchmark datasets (RefCOCO, RefCOCO+, RefCOCOg, ReferItGame and Flickr30K Entities) demonstrate that the proposed unified network outperforms or is on par with many existing task-customized models. Codes are available at https://github.com/LFUSST/MMI-VG.

Caracteristicile limbajului de lemn în comunicarea economică și tehnică

Wooden language, a complex phenomenon in economic and technical communication, represents a significant issue in the field of professional discourse. This study investigates the origin, evolution, and characteristics of wooden language, highlighting the need for clarity and conciseness in technical and economic communication. By analyzing examples and arguments, the research focuses on the impact of this type of jargon on understanding and communication efficiency. The results of this study make significant contributions to improving professional communication, emphasizing the importance of eliminating confusion and veiled expression in the use of abstract terms. This research proves to be a valuable tool for professionals in the economic and technical fields, promoting more efficient and accessible communication in these domains.

Online Self-Presentation by Traditional Chinese Medicine and Western Medicine Medical Professionals in China

ABSTRACT Despite increasing research that examines language features of online medical consultation (OMC) conversations in China, limited attention has been directed to how medical professionals purposefully present themselves in their biographies on OMC websites, an emerging genre of health communication, with even fewer comparative studies on traditional Chinese medicine (TCM) and Western medicine (WM) medical professionals in this regard. To fill these gaps, this study compares the personal claims and self-presentational strategies used in TCM and WM medical professionals’ biographies on a Chinese OMC website. It is found that while Chinese TCM and WM medical professionals present themselves in similar ways, they also demonstrate some important differences. The similarities may be driven by their shared goal of building trust in the OMC context, whereas the differences may be ascribed to TCM-WM differences in clinical philosophies, education histories, clinical cultures, and medical practices.

Computational analysis of linguistic features in speech samples of first-episode bipolar disorder and psychosis

BackgroundIn recent years, automated analyses using novel NLP methods have been used to investigate language abnormalities in schizophrenia. In contrast, only a few studies used automated language analyses in bipolar disorder. To our knowledge, no previous research compared automated language characteristics of first-episode psychosis (FEP) and bipolar disorder (FEBD) using NLP methods. MethodsOur study included 53 FEP, 40 FEBD and 50 healthy control participants who are native Turkish speakers. Speech samples of the participants in the Thematic Apperception Test (TAT) underwent automated generic and part-of-speech analyses, as well as sentence-level semantic similarity analysis based on SBERT. ResultsBoth FEBD and FEP were associated with the use of shorter sentences and increased sentence-level semantic similarity but less semantic alignment with the TAT pictures. FEP also demonstrated reduced verbosity and syntactic complexity. FEP differed from FEBD in reduced verbosity, decreased first-person singular pronouns, fewer conjunctions, increased semantic similarity as well as shorter sentence and word length. The mean classification accuracy was 82.45 % in FEP vs HC, 71.1 % in FEBD vs HC, and 73 % in FEP vs FEBD. After Bonferroni correction, the severity of negative symptoms in FEP was associated with reduced verbal output and increased 5th percentile of semantic similarity. LimitationsThe main limitation of this study was the cross-sectional nature. ConclusionOur findings demonstrate that both patient groups showed language abnormalities, which were more severe and widespread in FEP compared to FEBD. Our results suggest that NLP methods reveal transdiagnostic linguistic abnormalities in FEP and FEBD.

Research on the optimization of essay scores based on deep learning

Construct a scoring model based on shallow language features and deep language features, and combine multiple algorithms to optimize the effect of automatic scoring model for Chinese academic papers. Conduct research through literature review and interview research methods, analyze the impact and changes of optimizing academic paper systems combined with teacher feedback on students' writing learning. Create a model to identify elements in student writing, automatically segment, classify, and score the text in academic papers written by Chinese students. Optimizing academic paper systems can effectively improve students' ability to write academic papers, enhance students' writing motivation and interest, motivate students to revise their writing repeatedly, and enhance students' mastery of vocabulary, grammar, and technical details, as well as their writing motivation.

PERCEPTIONS OF THE RUSSIAN LANGUAGE IN THE MINDS OF TEACHERS OF RUSSIAN AS A FOREIGN LANGUAGE (Based on a Psycholinguistic Experiment)

The article describes the results of a psycholinguistic experiment aimed at identifying the perceptions of the Russian language in the minds of teachers of Russian as a foreign language. The specifi city of the experi-ment consists of the explicit professionally oriented character of the stimulus Russian language; during planning the experiment, the experience of similar studies with respondents-physicians was generalized of similar studies with respondents-philologists. One of the hypotheses, that preceded the experiment was the assumption that the teachers’ linguistic consciousness combines naive and scientifi c ideas about the Russian language in the teachers’ linguistic consciousness language. The experiment, built according to the free-chain model, was conducted in March–April 2023. The described material was extracted from 177 questionnaires, the total number of analyzed reactions is 1,185. In the fi rst stage of the analysis, the reactions were characterized in structural and grammati-cal aspect (predominantly one-word associations expressed by nouns), and at the second stage — in the semantic aspect. Semantic analysis of the associates allowed us to distinguish three semantic fi elds: “Russian language as an object of evaluation”, “Russian language as the basis of national Russian language as an object of evaluation”, “Russian language as the basis of national self-consciousness”, and “Russian language as an academic subject”. While analyzing the reactions that made up the fi rst fi eld, it proved expedient to refer to the typology of evalua-tive meanings proposed by N. D. Arutyunova. As a result, the predominance of private evaluative meanings in the fi eld was established of a wide spectrum. The second fi eld combines reactions based on their linguocultural potential: thus, the fi eld includes ethnonyms, culturally signifi cant toponyms, precedent phenomena, and symbol-ic words. The third fi eld most clearly represents the results of the work of professional linguistic consciousness and includes reactions of mainly terminological nature, correlated with linguistic concepts, sections of the course “Russian Language”, etc. The interpretation of the empirical material testifi es to the professionalization of the concept “Russian language” in the cognitive space of philologists and confi rms the hypothesis that associations refl ect the specifi cs of teaching Russian as a fo reign language, combining language teaching with immersion in Russian culture and intercultural communication. The respondents’ everyday perceptions include positive asso-ciative and evaluative meanings

Bank Emails: The Language of Legit and Scam

Amidst the pandemic, the surge in unsolicited scam emails has made internet technology a significant concern. Distinguishing between scams and authentic/legit emails has become increasingly difficult. This research aimed to identify typical characteristics and language patterns found in emails. It also aimed to identify the common linguistics and technical features of the scams and legitimate bank emails. Two legitimate emails and two scam or fraudulent emails from different banks in the Philippines (i.e., LandBank and BDO). A qualitative method was used to analyze and interpret the language features of the two emails. This led to the identification of shared characteristics found in scams and legitimate emails. A scam email typically includes embedded malicious links, misspellings, formatting issues, suspicious email domains, frequent use of contractions and redundancy, tautology, and imperative mood. On the other hand, legitimate emails exhibit proper punctuation, accurate email domains, appropriate formatting, absence of spelling mistakes, avoidance of contractions and redundancy, and use indicative mood rather than imperative. Scam emails utilize modal verbs to manipulate recipients into divulging personal information. Recognizing these email patterns is crucial for educating users and reducing phishing risks. It is important to note that the interpretation and findings of this study are based on the entire dataset collected. Keywords: Bank Emails, Legit Emails, Linguistic Features, Scam Emails, Phishing

ТИПОЛОГИЯ НЕКОТОРЫХ ЛЕКСИЧЕСКИХ ОСОБЕННОСТЕЙ АНГЛИЙСКОГО И РУССКОГО ЯЗЫКОВ В ТЕОРИИ КОММУНИКАТИВНОЙ КОМПЕТЕНЦИИ

Typology of some Lexical Features of English and Russian Languages in the Theory of Communicative competence Summary The article deals with a small comparative grammar analysis of English and Russian languages and reveals some aspects of communicative competence in the study of these languages. It also analyzes the most effective teaching methods for developing communicative competence. In the modern world, knowledge of foreign languages is becoming vital for a person. And from this point of view, the process of proper language teaching is important. Communicative competence plays a big role in learning foreign languages. In this article, we tried to give a small description of the theory of communicative competence by comparing some lexical features of English and Russian languages. Key words: language, communicative competence, linguistic competence, language competence

XARİCİ DİLİN TƏDRİSİNDƏ İNNOVATİV METODLARIN İSTİFADƏSİ

The Role of Innovative Methods in Teaching Foreign Languge Summary The article is devoted to description of innovative methods. Innovative methods and technologies of teaching today are gaining increasing recognition and new opportunities associated with the establishment of interpersonal interaction. In this article is paid attention to choices of methods which should vary with different purposes, ages groups, and stages of mental development. A structure of modern process of teaching and its results is presented in this receaerch. Some of the common learning characteristics of adult language and literacy learners as well as four guiding principles to teaching adults foreign languages are given in the article. Key words: innovative method, project, active learning, traditional learning, creative tasks

MƏTNDƏKİ BƏDİİ DİLİN TƏSİRLİ ÇATDIRILMASINDA OXUNUN ROLU

The Role of Reading in The Effective Transmission of Literary Language in Text Summary The artistic nature of literature, resulting from the figurativeness of words, leads to the formation of such a field as the art of words. Taking into account the peculiarities of artistic language in the text when reading, giving life to words, touching the human soul largely depends on the smooth and expressive reading of works. The specificity of the form of existence of the artistic word depends on taking into account the characteristics of the artistic language when reading the fact that it gives endless beauty to works in this area, reflects the artist’s colors in the word, and resembles the human soul. In the process of learning to read texts, one cannot be satisfied with the ability of students to express their opinions in a communicative way. At the same time, the content of the work should not mean only a coherent idea. Because the text may be a story with communication, but it does not evoke any feelings in the other side, it does not excite him. So, in addition to communication, storytelling should include figurative language and expressiveness. Key words: reading text, artistic features of language, artistic expression, imagery, expressive reading

A Logical Approach to Type Soundness

Type soundness, which asserts that “well-typed programs cannot go wrong”, is widely viewed as the canonical theorem one must prove to establish that a type system is doing its job. It is commonly proved using the so-called syntactic approach (aka progress and preservation ), which has had a huge impact on the study and teaching of programming language foundations. Unfortunately, syntactic type soundness is a rather weak theorem. It only applies to programs that are well-typed in their entirety, and thus tells us nothing about the many programs written in “safe” languages that make use of “unsafe” language features. Even worse, it tells us nothing about whether type systems achieve one of their main goals: enforcement of data abstraction. One can easily define a language that enjoys syntactic type soundness and yet fails to support even the most basic modular reasoning principles for abstraction mechanisms like closures, objects, and abstract data types. Given these concerns, we argue that programming languages researchers should no longer be satisfied with proving syntactic type soundness, and should instead start proving semantic type soundness , a more useful theorem which captures more accurately what type systems are actually good for. Semantic type soundness is an old idea—Milner’s original account of type soundness from 1978 was semantic—but it fell out of favor in the 1990s due to limitations and complexities of denotational models. In the succeeding decades, thanks to a series of technical advances—notably, step-indexed Kripke logical relations constructed over operational semantics, and higher-order concurrent separation logic as consolidated in the Iris framework in Coq—we can now build (machine-checked) semantic soundness proofs at a much higher level of abstraction than was previously possible. The resulting “logical” approach to semantic type soundness has already been employed to great effect in a number of recent papers, but those papers typically (a) concern advanced problem scenarios that complicate the presentation, (b) assume significant prior knowledge of the reader, and (c) suppress many details of the proofs. Here, we aim to provide a gentler, more pedagogically motivated introduction to logical type soundness, targeted at a broader audience that may or may not be familiar with logical relations and Iris. As a bonus, we also show how logical type soundness proofs can easily be generalized to establish an even stronger relational property— representation independence —for realistic type systems.

Linguistic Analysis of Texts in Philological Research: The Use of Salesforce Einstein Artificial Intelligence

Artificial intelligence is beginning to spread to all fields of science, and philology, linguistics and literature are no exception. This intersection of technology and the humanities opens a new era of linguistic and literary analysis. The relevance lies in the fact that artificial intelligence offers innovative ways of understanding and interpreting texts. Linguistic analysis of texts is an important part of philological research, as it helps to uncover the meaning, style, and other elements of language use in texts. This study aims to explore the innovative technology of Salesforce Einstein Artificial Intelligence, which can be used for linguistic text analysis in philological research. Research methods include literature review, correlation analysis, social analysis, impact analysis, syntactic analysis, and factor analysis. The results of the work showed that the system deeply learns the language and learns to recognize and analyze various language features and emotions. The paper examines the technical and ethical aspects of Salesforce Einstein AI. A cross-sectional study allowed us to describe the technological capabilities of the system and to debate the problem of replacing the author with artificial intelligence from an ethical perspective. The authors conclude that linguistic text processing in philology has revolutionized the way authors interact with technology and has become a valuable tool in text analysis. Salesforce Einstein AI has opened up a whole new world of opportunities for the field of philology.

Mining software insights: uncovering the frequently occurring issues in low-rating software applications.

In today's digital world, app stores have become an essential part of software distribution, providing customers with a wide range of applications and opportunities for software developers to showcase their work. This study elaborates on the importance of end-user feedback for software evolution. However, in the literature, more emphasis has been given to high-rating & popular software apps while ignoring comparatively low-rating apps. Therefore, the proposed approach focuses on end-user reviews collected from 64 low-rated apps representing 14 categories in the Amazon App Store. We critically analyze feedback from low-rating apps and developed a grounded theory to identify various concepts important for software evolution and improving its quality including user interface (UI) and user experience (UX), functionality and features, compatibility and device-specific, performance and stability, customer support and responsiveness and security and privacy issues. Then, using a grounded theory and content analysis approach, a novel research dataset is curated to evaluate the performance of baseline machine learning (ML), and state-of-the-art deep learning (DL) algorithms in automatically classifying end-user feedback into frequently occurring issues. Various natural language processing and feature engineering techniques are utilized for improving and optimizing the performance of ML and DL classifiers. Also, an experimental study comparing various ML and DL algorithms, including multinomial naive Bayes (MNB), logistic regression (LR), random forest (RF), multi-layer perception (MLP), k-nearest neighbors (KNN), AdaBoost, Voting, convolutional neural network (CNN), long short-term memory (LSTM), bidirectional long short term memory (BiLSTM), gated recurrent unit (GRU), bidirectional gated recurrent unit (BiGRU), and recurrent neural network (RNN) classifiers, achieved satisfactory results in classifying end-user feedback to commonly occurring issues. Whereas, MLP, RF, BiGRU, GRU, CNN, LSTM, and Classifiers achieved average accuracies of 94%, 94%, 92%, 91%, 90%, 89%, and 89%, respectively. We employed the SHAP approach to identify the critical features associated with each issue type to enhance the explainability of the classifiers. This research sheds light on areas needing improvement in low-rated apps and opens up new avenues for developers to improve software quality based on user feedback.

Detection and classification of threats and vulnerabilities on hacker forums based on machine learning

The object of this study is the process of detecting threats and vulnerabilities in hacker forums, which are a well-known source of potential dangers for Internet users. However, the problem of analyzing and classifying data from these forums is its complexity due to such features of the participants' language as specific slang, jargon, etc., which requires the use of modern tools of their processing. This paper explores the application of machine learning to devise an effective method for analyzing sentiment and trends in hacker forums to identify potential threats and vulnerabilities in cyberspace. All necessary stages of the process of detecting threats and vulnerabilities have been developed, ranging from data collection and preprocessing to the training of a model that is capable of processing “raw” unstructured data from hacker forums. The implementation of six popular machine learning algorithms, namely k Nearest Neighbors (kNN), Random Forest, Naive Bayes, Logistic Regression, Support Vector Machines (SVM), and Decision Tree algorithms have been studied with a view to determining their efficiency of threat and vulnerability detection and classification. The experiments have been conducted on real data (150,000 messengers). It has been determined that the Random Forest algorithm coped with the task the best (accuracy=0.89, recall=0.84, precision=0.91, F1-score=0.87 and ROC-AUC=0.89). The proposed tool based on machine learning not only collects data that poses a potential threat but also processes and classifies it according to the specified keywords. This allows detecting threats and vulnerabilities at a high speed. The results of the study make it possible to identify potential trends in threats and vulnerabilities. This will contribute to the improvement of cybersecurity systems and ensure more reliable protection of information resources

Analysis on the Artistic Style of Chinese Printmaking (1980 - 2000)

In the twenty-first century, Chinese printmaking has evolved towards introspection and integration with contemporary cultural landscapes. To analyze the development of Chinese printmaking in the past decade. The study used bibliographic review and analysis of printmaking exhibitions, artworks, and theoretical frameworks. Over the past decade, Chinese printmaking has shown increased activity, evolving its own contemporary language and ecological features. Exhibitions like the National Printmaking Exhibition and Mission Hills International Printmaking Biennale have been crucial in this development. Chinese printmaking has successfully revitalized its ontological language, establishing a distinctive aesthetic and cultural identity that responds to contemporary challenges.

ExaAUAC: Arabic Twitter user age prediction corpus based on language and metadata features

Twitter is a rich resource for analyzing the contents of social media and extracting the age groups of users can be beneficial for recommender systems, marketing and advertising. Age detection task is an aspect of demographic information of users. In this study a large-scale corpus of Arabic Twitter users including 181k user profiles with diverse age groups consisting of −18, 18–24, 25–34, 35–49, 50–64, +65 is presented. The corpus is created by four methods: (1) collecting publicly available birthday announcement tweets using the Twitter Search application programming interface, (2) augmenting data, (3) fetching verified accounts, and (4) manual annotation. To have a best age detection model on the presented corpus, different evaluations are tested to find the model with highest accuracy and efficiency. Number of tweets, regression vs. classification, using metadata of users and tweets, using LSTM+CNN model vs. BERT are some parts of examinations done. Presented methodology is based on language and metadata features and final model is fine-tuned with BERT on 70k users and evaluated on 8200 manually annotated users. We show that our best model, compared with LSTM+CNN model and BERT-based similar model yields an improvement of up to 9% in F1-score and increment of 5% in accuracy, respectively. The model achieved macro-averaged F1-score of 44 on six age groups, and F1-score of 58 on three age groups of −25, 25–34, +35. The link of our proposed data is provided here: www.github.com/exaco/ExaAUAC.

Соотношение языковой и этнической идентификации

The proposed article is devoted to the substantiation of the introduction into scientific use of the concept “linguoethnos”, defined as an association of people for whom a certain language is their native one. This concept is used as a basis for identifying possible types of correlation between linguistic and ethnic identification of a person: linguoethnos establishes the peculiarities of the implementation of ethnic self-determination in relation to the linguistic identity of a person. The definition of the linguoethnos is based on the concepts of “national language” and “native language”. In this concept, the national language is a complex of idioms associated with one ethnic group, for which one linguonym is used as a hyperonym. The article describes the situations of the formation of a superordinate linguoethnos combining several basic linguoethnoses that use different national variants of the same language, and the lack of a linguonymic definition of an idiom. Peripheral characteristics of the national language are “the presence of a literary form of existence” and “the presence of an official status.” When describing the features of the first characteristic, the situation of linking several literary standards with one national language is considered separately: geographically loose (Bukmol and Nynorsk in Norway) and geographically fixed (Mari meadow, Gornomari and northwestern Mari in Mari El). The latter case is interpreted as a situation of formation of a superordinate linguistic ethnos. When describing the second characteristic, a list of official language statuses is given (state, official language of the province, regional language). Two approaches to the definition of a native language are stated: constructivist (native language is the language of my nation) and primordial (native language is functionally the first language of an individual). The primordial approach is considered the only acceptable one for determining the linguoethnos, since it takes into account the deep connection of language with ethnic identity. Two types of relations between linguoethnos and ethnos are established: isomorphic (basic, transformed and selective) and non-isomorphic (genetic and opportunistic).

Hallucinations in automated texts – A critical view on the emerging terminology

The term hallucination is used in AI discourse to describe AI-generated outputs that are unfounded and lack backing in input data, a phenomenon which occurs frequently enough for the academic community to shun widespread collaboration with AI writing tools, particularly in certain disciplines. The issue of hallucinatory outputs will diminish as AI advances, but the appropriateness of using the terms hallucinate and hallucination in this context remains under debate. Originating from Latin, terms related to hallucination were once exclusively used within specialized medical terminology. Over time, and across languages, its metaphorical meaning has evolved, becoming part of colloquial language through the semantic innovation characteristic of youth language. We also show how this trend coincides with the use of metaphors such as anthrophomorphisms in scientific discourse. The newest addition to hallucination’s list of meanings – an established metaphor for a new phenomenon – is contentious. On the one hand, there is a similarity in that both AI-induced and medically induced hallucinations are elusive and difficult to identify. On the other hand, it suggests a trivialization of medical conditions that remain significantly stigmatized in contemporary societies.

THE IMPACT OF THE ETYMOLOGICAL STUDY OF THE CONSTITUENTS OF THE CONCEPT LANGUAGE POLICY ON THE FORMATION OF A CONCEPTUAL METAPHOR

The article is dedicated to the study of the semantic features of the constituent lexemes language and policy in the English worldview, which are analysed as components of the concept LANGUAGE POLICY, as well as the peculiarities of their influence on the formation of aconceptual metaphor. It has been established that the word combination language policy is rarely found in general language dictionaries, so it is appropriate to study its lexemes-constituents by their origin in order to find out how their cognitive components interact with each other. 17 and 22 definitions of the lexeme-constituents language and policy have been analysed, respectively. It is noted that the cognitive component a course of action of the lexeme-constituent policy explains the meaning of policy as directed actions on this or that issue. Cognitive components body of words; body of methods of combination of words and used by a nation, people, or race of the lexemes-constituent language explain language as a grouping of words, methods of their combination used by people. It has been established that the expediency of such an analysis consists in a detailed study of the verbalizers of the nominative field of the concept LANGUAGE POLICY. This requires a comprehensive analysis of the concept, taking into account qualitative and quantitative studies. Several conceptual metaphors are identified such as ECOLOGY, LANGUAGE PLANNING IS AN ORGAN, LANGUAGE IS STATUS, LANGUAGE IS FIGHT,MULTILINGUALISM IS MOSAIC, MULTILINGUALISM IS CONSTELLATION and LANGUAGE IS A FLOWER.It was noted that the etymological analysis of the combination of lexemes-constituents narrowed the meaning of lexemes in such a combination, which affected the LANGUAGE POLICY conceptual metaphor.

TRANSLATION STRATEGIES RELATED TO THE OMISSION OF VERBS WHEN TRANSLATING FROM RUSSIAN INTO FRENCH

While there is a vast literature on translation transformations and techniques, little attention among Russian researchers is paid to the omission. The article attempts to contribute to the debate by analyzing the omission as a translation technique, as well as verb omission examples when translating a literary text from Russian into French. The omission means elimination of a source text (ST) element while translating into target text. The omission can occur at the semantic or structural-semantic levels. The latter implies not only semantic but also syntactic changes. The omission can be due to the redundancy of an element in the ST. Redundancy in ST can be caused by the structural features of the source language, repetition of information in the text or by the opportunity to extract information from the situational context. The analysis of examples of verb omission taken from the translations into French of the novel Oblomov written by Ivan Goncharov showed that the use of this technique in relation to Russian verbs obeys the general patterns of the use of omission listed above: a French translator can omit a verb and use a more economical construction allowed by the norms of the French language; can translate one verb from two ST verbs with the same meaning; can eliminate the original verb if it’s meaning can be derived from the situational context. However, the original verb can convey stylistic meanings that are important in the work; if this verb is omitted, stylistic meanings disappear.