LKMT:Linguistics Knowledge-Driven Multi-Task Neural Machine Translation for Urdu and English

Thanks to the strong representation capability of pre-trained language models,supervised machine translation models have achieved outstanding performance.However,the performances of these models drop sharply when the scale of the parallel training corpus is limited.Considering the pre-trained language model has a strong ability for monolingual representation,it is the key challenge for machine translation to construct the in-depth relationship between the source and target language by injecting the lexical and syntactic information into pre-trained language models.To alleviate the dependence on the parallel corpus,we propose a Linguistics Knowledge-Driven MultiTask(LKMT)approach to inject part-of-speech and syntactic knowledge into pre-trained models,thus enhancing the machine translation performance.On the one hand,we integrate part-of-speech and dependency labels into the embedding layer and exploit large-scale monolingual corpus to update all parameters of pre-trained language models,thus ensuring the updated language model contains potential lexical and syntactic information.On the other hand,we leverage an extra self-attention layer to explicitly inject linguistic knowledge into the pre-trained language model-enhanced machine translation model.Experiments on the benchmark dataset show that our proposed LKMT approach improves the Urdu-English translation accuracy by 1.97 points and the English-Urdu translation accuracy by 2.42 points,highlighting the effectiveness of our LKMT framework.Detailed ablation experiments confirm the positive impact of part-of-speech and dependency parsing on machine translation.

Exploring Nominalization in English Abstracts of Applied Linguistics Research Articles:A Comparative Study Between Chinese and International Journals

Researchers around the world strive to communicate new knowledge,primarily via publication,with the abstract being crucial in conveying core insights.Previous research has generally analyzed the discourse features of abstracts from a macro perspective and often employed either outdated texts,such as those over a decade old,or papers written by authors with lower English academic writing proficiency as research material.In this study,we analyzed forty abstracts from leading journals in applied linguistics,evenly split between Chinese and international journals.It revealed that the use of nominalization in abstracts by Chinese and international scholars showed similarities due to the universal academic requirement for conciseness.However,due to cultural and educational differences,each group differed in their respective language choices and nominalization usage.By analyzing the application of nominalization in different cultural contexts,the results of our study offered practical suggestions for crafting abstracts that effectively convey information,thereby,contributing to the broader academic community.

Review of Accessing Academic Discourse:Systemic Functional Linguistics and Legitimation Code Theory

Accessing Academic Discourse:Systemic Functional Linguistics and Legitimation Code Theory,was edited by J.R.Martin,Karl Maton and Y.J.Doran and published by Routledge in 2020.This volume explores the dialogue with Legitimation Code Theory(LCT)from the viewpoint of systemic functional linguistics(SFL).“Systemic functional linguistics(SFL)is a long-established and widely known approach to understanding language.Legitimation Code Theory(LCT)is a younger and rapidly growing approach to exploring and shaping knowledge practices”(p.1).They have become widely used to access academic discourse by a growing number of systemic scholars and educators.

Cultural Linguistics and Intercultural Communication

The relationship between language and culture is the core issue in intercultural communication.For native language learners,their native language and local culture are in perfect harmony;while for foreign language learners,they often unconsciously separate the two,resulting in the phenomenon of“half-cooked rice”in foreign language education.This phenomenon makes us reflect on the purpose,content,and methods of foreign language education and seek theoretical guidance.Foreign language teaching aims to improve intercultural competencies,so it must face language and culture in intercultural communication.As a branch of cultural linguistics with multidisciplinary origins,intercultural linguistics focuses on the relationship between language and culture in intercultural communication.In the process of exploring how to apply linguistic theories in second language acquisition,it shows that intercultural linguistics not only has important enlightenment and application value,but also needs further studies.

Visualizing Aphasia in Linguistics From 2000 to 2019

This paper aims to visualize the research of aphasia from a linguistic perspective for the two decades from 2000 to 2019,identifying the changes in research focus and the future emerging trends of aphasia studies in linguistics.Applying the bibliometric approach,the present study reviewed 3,004 publications with the topic word“aphasia”in the framework of linguistics.The dataset was created from the Web of Science database ranging from 2000 to 2019.Using the CiteSpace tool,document co-citation analysis,betweenness centrality(BC)measurement and citation burst detection were conducted to explore and determine the thematic patterns,critical studies,and emerging trends of this knowledge domain.Twelve thematic patterns in these two decades were identified,indicating that researchers have focused on language impairment in aphasia,aphasia therapy and other topics associated with aphasia.Meanwhile,papers with high BC reveal the connections among different research clusters.In addition,bursts of detected citations demonstrate that treatment aiming at the enhanced quality of daily life,the utilization of discourse tasks and treatments at the discourse level,deeper exploration of primary progressive aphasia in terms of clinical data and the application of working memory assessment,and the role of working memory(WM)training in rehabilitation will possibly attract more attention in the future.On the basis of the cluster landscape,BC and citation bursts,the review found that scholars paid extensive attention to the alleviation of communication deficits in the linguistic exploration of aphasia.

The Application of Embodied Cognitive Linguistics in the English Translation of Two-Part Allegorical Saying—An Analysis of Examples From A Dream of Red Mansions

As a kind of widely circulated folk language,two-part allegorical saying(“xiehouyu”)carries the wisdom of the Chinese people and is characterized with humor and vivid imagery.Taking the two English translation versions of A Dream of Red Mansions as examples,this paper analyzes the English translation of two-part allegorical saying based on the core principle of Embodied Cognitive Linguistics(ECL),“Reality-Cognition-Language”,and explores how the English translation of two-part allegorical saying reflects the three dimensions of ECL.

A Study on the Utilization of Applied Linguistics in Contemporary English Teaching

In the context of globalization,the importance of teaching English as a common language in the world becomes increasingly apparent.Applied Linguistics belongs to one of the sub-disciplines of linguistics,which plays an important role in contemporary English teaching.The knowledge of applied linguistics can help students learn the grammar,semantics,vocabulary,writing,and other contents in English,deepen their knowledge and understanding of English,and enhance the effectiveness of English teaching.This paper mainly describes the important role played by English linguistics in English teaching and focuses on its utilization strategies in the hope of providing references on this topic.

A Study of English Grammar Teaching and Cultural Introduction from the Perspective of Applied Linguistics

Grammar teaching is the main content of university English teaching,and the quality of teaching will affect the effect of university talent cultivation.Based on the perspective of applied linguistics,it is crucial to use cultural introduction teaching for English grammar teaching.This paper will combine the basic concepts of applied linguistics and cultural introduction teaching,analyze the role of using the cultural introduction teaching method to innovate grammar teaching mode under the perspective of applied linguistics,and put forward a scientific English grammar teaching strategy with the goal of improving teaching quality.

The Application and Effect Evaluation of Corpus Linguistics in English Teaching

This paper explores the application and effect evaluation of corpus linguistics in English teaching.It first introduces the basic concepts and development history of corpus linguistics,then analyzes its connection with language teaching theories,discussing the advantages and challenges of using corpora in language teaching.Next,it delves into the methods and technologies for building and utilizing corpora,as well as their role in developing teaching resources.Lastly,within the framework and methods of teaching effect evaluation,specific application cases of corpus linguistics in teaching design are analyzed,and their effects are assessed.Recommendations for teaching improvement and future development directions are also proposed.

Sine Cosine Optimization with Deep Learning-Based Applied Linguistics for Sentiment Analysis on COVID-19 Tweets

Applied linguistics is an interdisciplinary domain which identifies,investigates,and offers solutions to language-related real-life problems.The new coronavirus disease,otherwise known as Coronavirus disease(COVID-19),has severely affected the everyday life of people all over the world.Specifically,since there is insufficient access to vaccines and no straight or reliable treatment for coronavirus infection,the country has initiated the appropriate preventive measures(like lockdown,physical separation,and masking)for combating this extremely transmittable disease.So,individuals spent more time on online social media platforms(i.e.,Twitter,Facebook,Instagram,LinkedIn,and Reddit)and expressed their thoughts and feelings about coronavirus infection.Twitter has become one of the popular social media platforms and allows anyone to post tweets.This study proposes a sine cosine optimization with bidirectional gated recurrent unit-based senti-ment analysis(SCOBGRU-SA)on COVID-19 tweets.The SCOBGRU-SA technique aimed to detect and classify the various sentiments in Twitter data during the COVID-19 pandemic.The SCOBGRU-SA technique follows data pre-processing and the Fast-Text word embedding process to accomplish this.Moreover,the BGRU model is utilized to recognise and classify sen-timents present in the tweets.Furthermore,the SCO algorithm is exploited for tuning the BGRU method’s hyperparameter,which helps attain improved classification performance.The experimental validation of the SCOBGRU-SA technique takes place using a benchmark dataset,and the results signify its promising performance compared to other DL models.

Chinese Journal of Applied Linguistics Call for Papers

The journal Chinese Journal of Applied Linguistics (CJAL) is the official journal of China English Language Education Association (CELEA),the Chinese affiliate of AILA (International Association of Applied Linguistics).It was initiated in 1978 as the only English language journal in China in the area of applied linguistics.Prof.Wen Qiufang from Beijing Foreign Studies University,former President of CELEA,serves as the current editor-in-chief.

Computational Linguistics with Optimal Deep Belief Network Based Irony Detection in Social Media

Computational linguistics refers to an interdisciplinary field associated with the computational modelling of natural language and studying appropriate computational methods for linguistic questions.The number of social media users has been increasing over the last few years,which have allured researchers’interest in scrutinizing the new kind of creative language utilized on the Internet to explore communication and human opinions in a betterway.Irony and sarcasm detection is a complex task inNatural Language Processing(NLP).Irony detection has inferences in advertising,sentiment analysis(SA),and opinion mining.For the last few years,irony-aware SA has gained significant computational treatment owing to the prevalence of irony in web content.Therefore,this study develops Computational Linguistics with Optimal Deep Belief Network based Irony Detection and Classification(CLODBN-IRC)model on social media.The presented CLODBN-IRC model mainly focuses on the identification and classification of irony that exists in social media.To attain this,the presented CLODBN-IRC model performs different stages of pre-processing and TF-IDF feature extraction.For irony detection and classification,the DBN model is exploited in this work.At last,the hyperparameters of the DBN model are optimally modified by improved artificial bee colony optimization(IABC)algorithm.The experimental validation of the presentedCLODBN-IRCmethod can be tested by making use of benchmark dataset.The simulation outcomes highlight the superior outcomes of the presented CLODBN-IRC model over other approaches.

Applied Linguistics with Mixed Leader Optimizer Based English Text Summarization Model

The term‘executed linguistics’corresponds to an interdisciplinary domain in which the solutions are identified and provided for real-time language-related problems.The exponential generation of text data on the Internet must be leveraged to gain knowledgeable insights.The extraction of meaningful insights from text data is crucial since it can provide value-added solutions for business organizations and end-users.The Automatic Text Summarization(ATS)process reduces the primary size of the text without losing any basic components of the data.The current study introduces an Applied Linguistics-based English Text Summarization using a Mixed Leader-Based Optimizer with Deep Learning(ALTS-MLODL)model.The presented ALTS-MLODL technique aims to summarize the text documents in the English language.To accomplish this objective,the proposed ALTS-MLODL technique pre-processes the input documents and primarily extracts a set of features.Next,the MLO algorithm is used for the effectual selection of the extracted features.For the text summarization process,the Cascaded Recurrent Neural Network(CRNN)model is exploited whereas the Whale Optimization Algorithm(WOA)is used as a hyperparameter optimizer.The exploitation of the MLO-based feature selection and the WOA-based hyper-parameter tuning enhanced the summarization results.To validate the perfor-mance of the ALTS-MLODL technique,numerous simulation analyses were conducted.The experimental results signify the superiority of the proposed ALTS-MLODL technique over other approaches.

Improved Attentive Recurrent Network for Applied Linguistics-Based Offensive Speech Detection

Applied linguistics is one of the fields in the linguistics domain and deals with the practical applications of the language studies such as speech processing,language teaching,translation and speech therapy.The ever-growing Online Social Networks(OSNs)experience a vital issue to confront,i.e.,hate speech.Amongst the OSN-oriented security problems,the usage of offensive language is the most important threat that is prevalently found across the Internet.Based on the group targeted,the offensive language varies in terms of adult content,hate speech,racism,cyberbullying,abuse,trolling and profanity.Amongst these,hate speech is the most intimidating form of using offensive language in which the targeted groups or individuals are intimidated with the intent of creating harm,social chaos or violence.Machine Learning(ML)techniques have recently been applied to recognize hate speech-related content.The current research article introduces a Grasshopper Optimization with an Attentive Recurrent Network for Offensive Speech Detection(GOARN-OSD)model for social media.The GOARNOSD technique integrates the concepts of DL and metaheuristic algorithms for detecting hate speech.In the presented GOARN-OSD technique,the primary stage involves the data pre-processing and word embedding processes.Then,this study utilizes the Attentive Recurrent Network(ARN)model for hate speech recognition and classification.At last,the Grasshopper Optimization Algorithm(GOA)is exploited as a hyperparameter optimizer to boost the performance of the hate speech recognition process.To depict the promising performance of the proposed GOARN-OSD method,a widespread experimental analysis was conducted.The comparison study outcomes demonstrate the superior performance of the proposed GOARN-OSD model over other state-of-the-art approaches.

Dart Games Optimizer with Deep Learning-Based Computational Linguistics Named Entity Recognition

Computational linguistics is an engineering-based scientific discipline.It deals with understanding written and spoken language from a computational viewpoint.Further,the domain also helps construct the artefacts that are useful in processing and producing a language either in bulk or in a dialogue setting.Named Entity Recognition(NER)is a fundamental task in the data extraction process.It concentrates on identifying and labelling the atomic components from several texts grouped under different entities,such as organizations,people,places,and times.Further,the NER mechanism identifies and removes more types of entities as per the requirements.The significance of the NER mechanism has been well-established in Natural Language Processing(NLP)tasks,and various research investigations have been conducted to develop novel NER methods.The conventional ways of managing the tasks range from rule-related and hand-crafted feature-related Machine Learning(ML)techniques to Deep Learning(DL)techniques.In this aspect,the current study introduces a novel Dart Games Optimizer with Hybrid Deep Learning-Driven Computational Linguistics(DGOHDL-CL)model for NER.The presented DGOHDL-CL technique aims to determine and label the atomic components from several texts as a collection of the named entities.In the presented DGOHDL-CL technique,the word embed-ding process is executed at the initial stage with the help of the word2vec model.For the NER mechanism,the Convolutional Gated Recurrent Unit(CGRU)model is employed in this work.At last,the DGO technique is used as a hyperparameter tuning strategy for the CGRU algorithm to boost the NER’s outcomes.No earlier studies integrated the DGO mechanism with the CGRU model for NER.To exhibit the superiority of the proposed DGOHDL-CL technique,a widespread simulation analysis was executed on two datasets,CoNLL-2003 and OntoNotes 5.0.The experimental outcomes establish the promising performance of the DGOHDL-CL technique over other models.

新文科背景下中国语言学学科的承继与发展

中国语言学自先秦以来,不仅取得丰硕的成果,而且形成独特的研究传统。近现代之后,中国语言学逐步转型,学科细分所致的新的研究态势已经不能适应新时代新文科要求。中国语言学需要在承继优良学术传统的基础上,面向人工智能和数字技术,走“大语言学”发展之路。

社会认知语言学再思考

社会认知语言学是社会认知理论与认知语言学的结合,也是认知语言学的一种发展趋势。过去四十多年,认知语言学对概念表征和语言表征之间的关系进行了深入探讨,但是却忽视了言语交际的社会因素。针对认知语言学中出现的社会转向,我们近几年提出社会认知语言学这一新的学科,主要探讨社会认知如何影响语言的结构、表达和理解。本文主要阐释社会认知理论的有关问题以及人际层面、群际层面、社会实践认知层面的社会认知语言学视野。希望通过这些方面的阐释,能进一步明确社会认知语言学的内涵和研究范围,推动该领域的发展。

Critical Discourse Analysis Based on Halliday’s Systemic Functional Linguistics: Taking The Economist’s First Commentation on the End of China’s Zero-COVID Policy as an Example

Based on Halliday’s systemic functional grammar,especially the ideational function,this research aims at disclosing the hidden ideologies and values of the seemingly objective news reports on China’s COVID-19 policies in The Economist.Transitivity,voice,and nominalization are the major analytical subjects.After China lifted the zero-COVID policy,western media began criticizing China’s lack of data sharing,with some misinformation and misleading reports.The denouncement of inertness and reluctance to fight against the pandemic disclaim the Chinese government’s efforts and depreciate China’s image.China is portrayed as the villain and destroyer of people’s health worldwide.Meanwhile,they also hold a hesitant attitude toward China’s diplomacy.The re-engaging with foreign countries and travel restrictions have been described as imprudent and rushed actions.They also consider China as the fuse of contradiction in the United Nations.What is overt is their view of breaking up China.

失语症研究的语言学转向

失语症研究的发展经历了由医学主导到心理学主导,再到语言学主导,再到目前多学科交叉的变化过程。目前,在世界范围内从语言学视角开展失语症研究的热潮正在形成,主要包括失语症言语特征、失语症患者语言能力评估以及失语症的康复训练。本文从这三个视角介绍中西方失语症研究的概况,论述失语症研究需要开展的工作,尤其是我国失语症研究需要开展的工作,为我国语言学学者从事失语症研究指明方向。

《黄帝内经》节字含义缕析

目的基于语料库证据,通观解释《黄帝内经》中“节”字的含义,分类整理探析“节”的内涵。方法采用文献计量学的研究方法,对《黄帝内经》中的“节”字进行检索、统计、分析,对“节”字的数量、分布、功能等进行定量、定性汇总。结果《黄帝内经》中的“节”动静皆宜,动指调节生命的节律,静则具象为关节骨节,与天人相应理论相合。结论《黄帝内经》时代对“节”的理解基于天人相应理论,现代趋向于将“节”字的含义延伸至生命节律、神经通路等多元化高级通路的概念层面。