Chinese Language Research Articles

Chinese Named Entity Recognition Based on Multi-Level Representation Learning

Named Entity Recognition (NER) is a crucial component of Natural Language Processing (NLP). When dealing with the high diversity and complexity of the Chinese language, existing Chinese NER models face challenges in addressing word sense ambiguity, capturing long-range dependencies, and maintaining robustness, which hinders the accuracy of entity recognition. To this end, a Chinese NER model based on multi-level representation learning is proposed. The model leverages a pre-trained word-based embedding to capture contextual information. A linear layer adjusts dimensions to fit an Extended Long Short-Term Memory (XLSTM) network, enabling the capture of long-range dependencies and contextual information, and providing deeper representations. An adaptive multi-head attention mechanism is proposed to enhance the ability to capture global dependencies and comprehend deep semantic context. Additionally, GlobalPointer with rotational position encoding integrates global information for entity category prediction. Projected Gradient Descent (PGD) is incorporated, introducing perturbations in the embedding layer of the pre-trained model to enhance stability in noisy environments. The proposed model achieves F1-scores of 96.89%, 74.89%, 72.19%, and 80.96% on the Resume, Weibo, CMeEE, and CLUENER2020 datasets, respectively, demonstrating improvements over baseline and comparison models.

Measuring Instruments for Media Health Literacy: A Systematic Review of Psychometric Properties.

A systematic review of the scientific literature was performed in 2023. The articles were extracted from the electronic databases "Pubmed", "Web of Science", "Dialnet", and "Scopus". The search languages were limited to English, Spanish, and Portuguese. Twelve articles were selected for further analysis. The described measurement instruments included five original scales and seven cross-cultural adaptations of three of them. Four scales (the Sugar-Sweetened Beverages Media Literacy scale adapted to Turkish and Chinese, along with the Media Health Literacy (MeHLit) scale and its adaptation to the Chinese language) exhibited high quality in the assessment of psychometric properties. These instruments allow for the measurement of an individual's level of skill when consuming specific health information, enabling an analysis to understand the risk they are exposed to. Further research is recommended to strengthen the existing evidence and apply these tools to broader and more diverse populations.

7056 Can ChatGPT Educate Multicultural Patients About Metabolic Syndrome?

Abstract Disclosure: G. Wu: None. E. Cheng: None. V.V. Toram: None. K. Rosen: None. A. Wong: None. W. Zhao: None. M. Del Buono: None. Background: Metabolic Syndrome, which affects Asians, is a major risk factor for diabetes. According to the National Institute of Health (NIH), 1 in 3 Americans have Metabolic Syndrome. Diabetes affects 30 million Americans, and 8 million more are undiagnosed. ChatGPT and Bard are Artificial Intelligence (AI) mediated LLMs launched on 11/30/2022 and 3/21/2023, respectively, that generate real-time conversational responses. Purpose: Can ChatGPT educate our multicultural patients about metabolic syndrome? Methods: 1. User prompt into ChatGPT and Bard: What is metabolic syndrome? I am a South Asian male, 40 years old, with a cholesterol level of 250 and a fasting blood sugar level of 120. The exact prompt was used with an Asian male as a substitute. 2. The prompt was translated into Telugu, Hindi, Simplified Chinese, and Traditional Chinese via Google Translate. 3. Flesch-Kincade (FK) method of ascertaining reading level was used. FK is used by the US Department of Education. Results: Flesch-Kincaid reading ease: ChatGPT: English=29.2, Telugu=60.1, Hindi=33.4, Chinese (Trad.)=14.5, Chinese (Simp.)=22.6 Bard: English=35.3, Telugu=52, Hindi=51.7, Chinese (Trad.)=52, Chinese (Simp.)=36.8 Language Group Comparison to English: ChatGPT: Indian Languages p=0.004; Chinese Languages p=0.081. Bard: Indian Languages p=0.007; Chinese Languages p=0.136. Of note, the Telegu response has one incorrect response. Conclusions: In conclusion, ChatGPT and Bard can provide factual responses based on English prompts. Foreign prompts can yield inaccurate information. Physicians and their teams still need to supervise patient usage. Presentation: 6/2/2024

A mixed-methods investigation into complex components of multilingual international students' self-regulated learning in English as a foreign language context: A social cognitive perspective

Self-regulated learning serves as a fundamental framework for understanding the cognitive, motivational, and emotional dimensions of learning. Recently, a growing body of studies on such cognitive processes appears in multilingual populations. Applying a mixed-methods approach, this study examined the key components of the self-regulated learning process among 233 multilingual international students in China, specifically within the context of English as a Foreign Language learning. Qualitative data was analyzed through Pearson's correlation analysis, structural equation modeling, and path analysis, while semi-structured interviews were conducted to further confirm the results of the qualitative data analysis. 15 students were purposefully selected through purposive sampling to participate in follow-up interviews. Within the framework of social cognitive theory, the findings revealed that metacognition, motivation, self-efficacy, and feedback loops are the primary components of self-regulated learning. Additionally, path analysis confirmed that the four factors are positive predictors of self-regulated learning proficiency of multilingual international students in China. The interview outcomes further validated the integral role of these primary components in the self-regulated learning process within the context of multilingual study. This study underscores the significance of incorporating translanguaging backgrounds into teaching strategies and language policy. Findings may offer some insights for multilingual international students, language teachers, and language policymakers in the field of Chinese language instruction.

Beyond Granularity: Enhancing Continuous Sign Language Recognition with Granularity-Aware Feature Fusion and Attention Optimization

The advancement of deep learning techniques has significantly propelled the development of the continuous sign language recognition (cSLR) task. However, the spatial feature extraction of sign language videos in the RGB space tends to focus on the overall image information while neglecting the perception of traits at different granularities, such as eye gaze and lip shape, which are more detailed, or posture and gestures, which are more macroscopic. Exploring the efficient fusion of visual information of different granularities is crucial for accurate sign language recognition. In addition, applying a vanilla Transformer to sequence modeling in cSLR exhibits weak performance because specific video frames could interfere with the attention mechanism. These limitations constrain the capability to understand potential semantic characteristics. We introduce a feature fusion method for integrating visual features of disparate granularities and refine the metric of attention to enhance the Transformer’s comprehension of video content. Specifically, we extract CNN feature maps with varying receptive fields and employ a self-attention mechanism to fuse feature maps of different granularities, thereby obtaining multi-scale spatial features of the sign language framework. As for video modeling, we first analyze why the vanilla Transformer failed in cSLR and observe that the magnitude of the feature vectors of video frames could interfere with the distribution of attention weights. Therefore, we utilize the Euclidean distance among vectors to measure the attention weights instead of scaled-dot to enhance dynamic temporal modeling capabilities. Finally, we integrate the two components to construct the model MSF-ET (Multi-Scaled feature Fusion–Euclidean Transformer) for cSLR and train the model end-to-end. We perform experiments on large-scale cSLR benchmarks—PHOENIX-2014 and Chinese Sign Language (CSL)—to validate the effectiveness.

The Construction and Application of Smart Teaching Model for Speaking in International Chinese Language Education

The Construction and Application of Smart Teaching Model for Speaking in International Chinese Language Education

Ecolinguistic dynamics of English loanwords in Chinese: a case study on terms for cement

Ecolinguistics explores the interplay between language and the environment, offering insights into how linguistic elements adapt and evolve. This study examines five cement-related English loanwords in Chinese to uncover the evolutionary mechanisms governing the adaptation of these loanwords by analyzing their ecological dynamics. The research quantitatively evaluates the ecology of these loanwords using two indicators: lexical niche breadth and overlap. The results are as follows: (1) The emergence of English loanwords in Chinese is intricately linked to specific social environments. As new concepts and items are introduced from abroad, the masses initially coin new loanwords, which are later standardized by authoritative bodies. (2) The vitality of the loanwords correlates with their niche breadth. The competition among lexical variants is influenced by niche overlap. The loanwords for cement are ranked by vitality values in descending order—ShuiNi (水泥/water mud): 3.221, YangHui (洋灰/foreign ash): 2.350, ShuiMenTing (水门汀/water-gate concrete): 1.385, HongMaoNi (红毛泥/red-hair clay): 1.202, and ShiMinTu (士敏土/sticky soil): 0.879. (3) The endangerment of the loanwords results from the synergistic interaction between external (nature, society, culture, psychology) and internal (sound, form, meaning, grammar) environments. Intense competition arises due to multiple synonyms for the same entity, and adaptation challenges occur when the loanwords do not precisely fit the entity. Among the five loanwords for cement, the first two exhibit higher vitality and continue to develop sustainably, while the last three show lower vitality and are gradually becoming endangered. As these loanwords undergo continuous evolution, a lexical ecocontinuum emerges: (i) extinct in the wild—ShiMinTu; (ii) critically endangered—HongMaoNi; (iii) endangered—ShuiMenTing; (iv) vulnerable—YangHui; (v) least concerned—ShuiNi.

The Emergence of the Modern Chinese Language: Four Studies - Chinese Grammatology: Script Revolution and Literary Modernity, 1916–1958 By Yurou Zhong. New York: Columbia University Press, 2019. xii + 279 pp. $105.00 (cloth), $25.00 (paper), $34.99 (eBook) - Dialect and Nationalism in China, 1860–1960 By Gina Anne Tam. Cambridge: Cambridge University Press, 2020. xii + 261 pp. $99.99 (cloth), $29.99

The Emergence of the Modern Chinese Language: Four Studies - Chinese Grammatology: Script Revolution and Literary Modernity, 1916–1958 By Yurou Zhong. New York: Columbia University Press, 2019. xii + 279 pp. $105.00 (cloth), $25.00 (paper), $34.99 (eBook) - Dialect and Nationalism in China, 1860–1960 By Gina Anne Tam. Cambridge: Cambridge University Press, 2020. xii + 261 pp. $99.99 (cloth), $29.99

DISCUSSING THE ISSUES OF BUILDING A SYSTEM OF TRAINING LOCAL CHINESE LANGUAGE TEACHERS IN KAZAKHSTAN

Under the framework of the Belt and Road Initiative, this study focuses on the construction and optimisation of the local Chinese language teacher education system in Kazakhstan. By examining in detail, the structure and function of the current system of Chinese language teacher training in Kazakhstan and the multiple challenges it faces, we use comparative pedagogical methods and refer to successful models of teacher education at home and abroad, with the aim of proposing a set of actionable strategic recommendations. These proposals aim not only to promote the professional growth and stability of local Chinese language teachers, but also to enhance the quality and effi-ciency of Chinese language teaching, thus promoting the popularisation and application of Chinese language in Kazakhstan. Srengthening international co-operation in the field of language education, especially exchanges with China, iscrucial for enhancing understanding and deepening the human-istic bond between the two peoples. Therefore, this study also aims to provide theoretical support and practical guidance for the construction of a shared linguistic and cultural platform connected two countries and promoted of the regional practice of the concept "community of human destiny", thus contributing to the pluralistic dialogue and harmonious coexistence among the countries along the "Belt and Road".

Rule-based fine-grained vocabulary for enhanced Chinese pre-training

Abstract Chinese pre-training is an essential direction in Chinese natural language processing, and vocabulary constitutes the foundation of pre-trained models. Existing methods for constructing vocabularies for Chinese pre-trained models typically treat each Chinese character as an indivisible token, overlooking the additional information embedded in the intrinsic structure of Chinese characters and its impact on model performance. To leverage this information, we propose a method of training with rule-based fine-grained vocabularies to directly learn the sequence of intrinsic structures of Chinese characters in Chinese pre-training. Specifically, we first construct a mapping rule-based fine-grained vocabulary based on the glyph and radical splitting mapping relationship of Chinese characters. Subsequently, we employ a whole char masking strategy to train Chinese pre-trained models based on this new vocabulary. Experimental results demonstrate that compared to the BERT baseline model, our model achieves promising performance on multiple downstream tasks, with fewer model parameters and stronger robustness. The proposed Chinese pre-training method exploits the intrinsic structural information of Chinese characters, providing a novel method for subsequent research in Chinese natural language processing.

A Corpus-Based Multifactorial Study of Help/help to Alternation in Learners’ Language: From the Perspective of Probabilistic Grammar

This corpus-based multifactorial study delves deeper into the well-known alternation between bare and full infinitive complements, specifically regarding the help concordances. It extends the line of research to learners’ language productions with a focus on comparing and contrasting the probabilistic grammatical knowledge reflected in the help/ help to choices, which are constrained by a complex network of factors. Regression modeling indicates that constraints such as the horror aequi and certain morphological forms of the verb help are comparatively stable among groups of Chinese English language learners and native English speakers. Therefore, the principle of cognitive complexity and the avoidance strategy fueling infinitive variations are further tested. While the object typology differs in effect strength, it also prompts consideration of cultural influences on the part of Chinese English learners. In addition, two different patterns of interaction effects are explored in each dataset, which implies that learners’ language choice is usage-based, determined by an unconscious assessment of multiple clues that are learned from language input and shaped by language experiences.

A representation learning-based approach to enhancing manufacturing quality for low-voltage electrical products

In low-voltage electrical product manufacturing, resolving quality issues is heavily reliant on engineering experience, and can be time-consuming and error-prone. Through quality management systems, a large number of historical defect cases can be consolidated for analysis along with relevant causes. However, these defect descriptions are often casually described with a mix of Chinese and English language, containing domain-specific terms. Additionally, defect product features have varieties and complex relationships. Therefore, historical defect cases have not been effectively utilized to support manufacturing quality issues. To address this challenge, this study proposes a representation learning-based approach to enhance manufacturing quality. Key research contributions include: (1) A two-stage word embedding technique based on the pre-trained language model. First, TSDAE is utilized for unsupervised pre-training on a large amount of unlabeled data. Then, Sentence-BERT is utilized for fine-tuning on a small set of labeled similar sentence pairs. This process yields a pre-trained language model specific to low-voltage electrical product defects. (2) NSHPSAGE graph embedding model based on the constructed product feature knowledge graph. We select more valuable neighboring nodes during sampling and explore different aggregation functions to enhance graph embedding performance. This model effectively aggregates product feature information into “Defect_Case” nodes, yielding graph embedding vectors. The model exhibits good Weighted-Precision and Weighted-Recall with a short training duration, and it can handle new nodes, addressing the issue of heterogeneous graph embedding. (3) A defect case recommendation technique that fuses word embedding and graph embedding. We use Multi-Head Attention Fusion in the late-fusion to obtain defect case vectors. This approach comprehensively considers defect description semantic knowledge and complex product feature relationships, enabling accurate defect case recommendation with the prototype system.

The Impact of Peer Feedback on L2 Literature Review Writing: A Mixed Methods Study

Research on how peer feedback affects second language (L2) writing in higher education has been limited. This study examines the impact of peer feedback on revision and literature review writing in learners of Chinese as an L2 at a university in mainland China. The study analyzed feedback, revisions, and writing performance of 30 students. The quantitative analysis revealed that revision-oriented feedback had significantly positive effects on revision. Adopted-feedback-revision explained the gain score in the writing performance. The qualitative text analysis demonstrated that students paid unbalanced attention to the genre-specific characteristics of the literature review and the concreteness varied accordingly. Students valued peer feedback for improving comprehension, thinking skills, and audience awareness, especially when it identified issues with specific revision suggestions. This study contributes to the field by addressing how Chinese language learners benefited from peer feedback when writing literature review in higher education, which also has practical implications.

The Application and Challenge of Chinese Folk Literature in International Chinese Language Education Under The Background of The Belt and Road Initiative

The Application and Challenge of Chinese Folk Literature in International Chinese Language Education Under The Background of The Belt and Road Initiative

Principled Eclecticism in Chinese Language Teaching: From A Comprehensive Review to Practice with Checklist Development

Principled Eclecticism in Chinese Language Teaching: From A Comprehensive Review to Practice with Checklist Development

Effectiveness of Computer Application in Improving Reading Skills in Chinese Language and Towards Post-Attitudes as Home-based Learning

Background: As technology continues to advance, language acquisition methodologies have increasingly been integrated into computer-assisted language learning (CALL) systems. In the context of Chinese language acquisition, characters are structured in three phases: the overall character, its components, and its strokes. Proficiency in identifying and distinguishing individual characters hinges upon understanding their structural composition. Objective: This study aims to explore the impact of a computer application on Chinese language reading skills and students' perceptions regarding the utilization of computer applications for home-based learning. Method: A total of 60 students engaged in home-based learning using a designated computer application were involved in the study. Employing a quantitative approach with a quasi-experimental design, the study assessed the effects of the intervention. Results and Conclusion: Following one month of home-based learning through computer applications, participants exhibited higher gain scores in reading skill tests, albeit the differences were not statistically significant. Students expressed a preference for and perceived greater ease in acquiring reading skills through computer applications compared to traditional methods. Furthermore, the integration of computer applications in teaching and learning processes demonstrated the potential to enhance students' motivation, interest, and confidence in language acquisition, albeit without a notable impact on attention levels. The study underscores the pedagogical promise of Computer-Assisted Language Learning (CALL) and advocates for further research endeavors in this domain.

북한이탈주민 대상 한국어 발음 양상 및 인식 연구

Objectives The purpose of this study is to help North Korean defectors settle in Korean society by analyzing the realization pattern and perception of Korean pronunciation for North Korean defectors and considering pronunciation education plans. Methods Accordingly, North Korean defectors who have settled in Korean society were interviewed to confirm differences in pronunciation and the necessity of education. Since the specificity of North Korean defectors was premised, qualitative research was conducted through the subjects. Results As a result, it was confirmed that North Korean defectors had difficulty living in Korean language, which was caused by ‘Chinese and foreign language use, accent differences, word differences, language etiquette and speech differences, pronunciation differences, and psychological atrophy’. In addition, the difference in Korean utterances of North Korean defectors was large in consonants and phonological rules, and vowels were weak. In particular, it was confirmed that there was a difference from pronunciation in Korea because cypress, palatine, ㄴ addition, and head law were not recognized as phonological rules in North Korea, so they were not marked and educated. Conclusions Through the research results, the goals and contents of Korean language education for North Korean defectors can be specified in the future and practical effects can be enhanced.

A Systematic Review of Effective Models in School-Enterprise Cooperation in China in the English and Chinese Literature

Against the backdrop of globalization and rapid technological development, the traditional Technical & Vocational Education (TVE) system is facing more and more challenges. As a rapidly developing economy, China is also exploring effective paths in combining education and industry. School-Enterprise Cooperation(S-EC), as an emerging education method, aims to realize the effective docking of education resources and market demand through close cooperation between schools and enterprises. At present, Chinese scholars have conducted extensive research on the model of S-EC, however, few systematic reviews of related studies were carried out. The purpose of this paper is to examine and assess the relevant literature concerning effective S-EC models in the last ten years from 2015 to 2024. The review includes sources in both Chinese and English languages. The author conducted individual assessments of titles, abstracts, and complete texts according to predefined eligibility criteria. 15 studies that met the eligibility criteria were included in the reviewed systematic review. Effective S-EC models mentioned in these articles can be summarized and classified into three types: School-led Model, Enterprise-led Model and School-Enterprise Cooperation Model, of which each is subordinate to 3-4 specific cooperation models.

The Specific Application of Poetry and Prose in Primary School Chinese Language Teaching

In primary school Chinese language teaching, ancient poetry accounts for a large proportion and is a key focus of Chinese language teaching. However, for elementary school students whose understanding ability is not yet fully mature, the implicit emotions and obscure content in ancient poetry are often difficult to understand, so teaching ancient poetry is also a difficult point in Chinese language teaching. The teaching of ancient poetry bears the responsibility of inheriting and promoting China s excellent traditional culture to a certain extent, so the teaching of ancient poetry should attract the attention and importance of teachers. Based on this, this study discusses the application value of poetry in primary school Chinese language teaching, analyzes the current problems in teaching, and proposes specific methods such as creating scenarios and enriching related activities, in order to provide reference and assistance for the application of poetry in primary school Chinese language teaching.

Model Construction of Chinese Language Teaching from the Perspective of Artificial Intelligence

With the evolution of the information age, artificial intelligence has become an important variable affecting future social development, and its educational value has been widely recognized. In 2018, the Ministry of Education's "Education Informatization 2.0 Action Plan" put forward higher requirements for teaching informatization. The integration of artificial intelligence and education is the only way to improve teaching quality and cultivate talents that adapt to the development of the times. The core of educational informatization is the intelligence of teaching, which makes teaching methods intelligent, educational communication intelligent, and teaching methods technological. In view of this, firstly, the basic characteristics of the teaching information model were analyzed; Secondly, the application of the Chinese language information model was analyzed; Once again, the implementation of the Chinese language information model was analyzed to explore the opportunities and challenges faced by improving the application of artificial intelligence; Finally, from the perspectives of schools and teachers, strategies and suggestions are proposed to improve Chinese language education and teaching from the perspective of artificial intelligence.