Research on Chinese Sign Language(CSL)provides convenience and support for individuals with hearing impairments to communicate and integrate into society.This article reviews the relevant literature on Chinese Sign La...Research on Chinese Sign Language(CSL)provides convenience and support for individuals with hearing impairments to communicate and integrate into society.This article reviews the relevant literature on Chinese Sign Language Recognition(CSLR)in the past 20 years.Hidden Markov Models(HMM),Support Vector Machines(SVM),and Dynamic Time Warping(DTW)were found to be the most commonly employed technologies among traditional identificationmethods.Benefiting from the rapid development of computer vision and artificial intelligence technology,Convolutional Neural Networks(CNN),3D-CNN,YOLO,Capsule Network(CapsNet)and various deep neural networks have sprung up.Deep Neural Networks(DNNs)and their derived models are integral tomodern artificial intelligence recognitionmethods.In addition,technologies thatwerewidely used in the early days have also been integrated and applied to specific hybrid models and customized identification methods.Sign language data collection includes acquiring data from data gloves,data sensors(such as Kinect,LeapMotion,etc.),and high-definition photography.Meanwhile,facial expression recognition,complex background processing,and 3D sign language recognition have also attracted research interests among scholars.Due to the uniqueness and complexity of Chinese sign language,accuracy,robustness,real-time performance,and user independence are significant challenges for future sign language recognition research.Additionally,suitable datasets and evaluation criteria are also worth pursuing.展开更多
(Aim)Chinese sign language is an essential tool for hearing-impaired to live,learn and communicate in deaf communities.Moreover,Chinese sign language plays a significant role in speech therapy and rehabilitation.Chine...(Aim)Chinese sign language is an essential tool for hearing-impaired to live,learn and communicate in deaf communities.Moreover,Chinese sign language plays a significant role in speech therapy and rehabilitation.Chinese sign language identification can provide convenience for those hearing impaired people and eliminate the communication barrier between the deaf community and the rest of society.Similar to the research of many biomedical image processing(such as automatic chest radiograph processing,diagnosis of chest radiological images,etc.),with the rapid development of artificial intelligence,especially deep learning technologies and algorithms,sign language image recognition ushered in the spring.This study aims to propose a novel sign language image recognition method based on an optimized convolutional neural network.(Method)Three different combinations of blocks:Conv-BN-ReLU-Pooling,Conv-BN-ReLU,Conv-BN-ReLU-BN were employed,including some advanced technologies such as batch normalization,dropout,and Leaky ReLU.We proposed an optimized convolutional neural network to identify 1320 sign language images,which was called as CNN-CB method.Totally ten runs were implemented with the hold-out randomly set for each run.(Results)The results indicate that our CNN-CB method gained an overall accuracy of 94.88±0.99%.(Conclusion)Our CNN-CB method is superior to thirteen state-of-the-art methods:eight traditional machine learning approaches and five modern convolutional neural network approaches.展开更多
Motivation is a key factor that influences the outcome of second language(L2)learning.Chinese as a second language(CSL)learners,however,may experience demotivation in their Chinese learning process which will,more oft...Motivation is a key factor that influences the outcome of second language(L2)learning.Chinese as a second language(CSL)learners,however,may experience demotivation in their Chinese learning process which will,more often than not,reduce their learning interest and eventually affect their learning effect,therefore,it is necessary to enhance the learners’motivation level.This article first reviews the research literature in motivation in general,then discusses the CSL learners’demotivation in their Chinses learning process studying in China.Finally,it introduces motivational strategies to activate CSL learners’motivation in learning Chinese.展开更多
This paper presents a systematic review of research on Chinese as a Second Language(CSL)education for ethnic minority students in Hong Kong SAR.Using three databases and screening with specific inclusion and exclusion...This paper presents a systematic review of research on Chinese as a Second Language(CSL)education for ethnic minority students in Hong Kong SAR.Using three databases and screening with specific inclusion and exclusion criteria,the study selected 38 empirical studies published in English-language peer-reviewed journals.We find that there has been a surge of publications in Hong Kong in the past decade(2010–2020),and they are mostly authored by scholars from three universities in Hong Kong.Most of the research took a phenomenological approach,using interviews as the main data collection method and focusing on underprivileged South Asian students in secondary schools.The thematic analysis showed that Hong Kong’s CSL adopted a poststructuralist paradigm for understanding and revealing social inequalities surrounding Chinese language education for ethnic minority students.The study concludes that Hong Kong must decolonise its education system to genuinely support ethnic minority students to achieve educational equality and social justice.展开更多
In this study, we made references to past literatures and developed an e-learning training program for CSL （Chinese as a Second Language） teachers. The class was held from July to August, 2010, in Chinese Culture Un...In this study, we made references to past literatures and developed an e-learning training program for CSL （Chinese as a Second Language） teachers. The class was held from July to August, 2010, in Chinese Culture University （Taiwan）, and we designed a performance-evaluation questionnaire with the Delphi method. Three months after the training program was completed, the questionnaire was given to the 30 students of the class, and they were asked to answer questions regarding their use of e-learning in the actual practice. We also asked 5 teachers to conduct experimental e-learning for us to video-record and observe. This effort allows us to discuss the use of e-learning among CSL teachers in Taiwan, come up with a conclusion and suggestions, and use the findings as references for course-planning and policies or research regarding the digital learning of Chinese.展开更多
基金supported by National Social Science Foundation Annual Project“Research on Evaluation and Improvement Paths of Integrated Development of Disabled Persons”(Grant No.20BRK029)the National Language Commission’s“14th Five-Year Plan”Scientific Research Plan 2023 Project“Domain Digital Language Service Resource Construction and Key Technology Research”(YB145-72)the National Philosophy and Social Sciences Foundation(Grant No.20BTQ065).
文摘Research on Chinese Sign Language(CSL)provides convenience and support for individuals with hearing impairments to communicate and integrate into society.This article reviews the relevant literature on Chinese Sign Language Recognition(CSLR)in the past 20 years.Hidden Markov Models(HMM),Support Vector Machines(SVM),and Dynamic Time Warping(DTW)were found to be the most commonly employed technologies among traditional identificationmethods.Benefiting from the rapid development of computer vision and artificial intelligence technology,Convolutional Neural Networks(CNN),3D-CNN,YOLO,Capsule Network(CapsNet)and various deep neural networks have sprung up.Deep Neural Networks(DNNs)and their derived models are integral tomodern artificial intelligence recognitionmethods.In addition,technologies thatwerewidely used in the early days have also been integrated and applied to specific hybrid models and customized identification methods.Sign language data collection includes acquiring data from data gloves,data sensors(such as Kinect,LeapMotion,etc.),and high-definition photography.Meanwhile,facial expression recognition,complex background processing,and 3D sign language recognition have also attracted research interests among scholars.Due to the uniqueness and complexity of Chinese sign language,accuracy,robustness,real-time performance,and user independence are significant challenges for future sign language recognition research.Additionally,suitable datasets and evaluation criteria are also worth pursuing.
基金supported from The National Philosophy and Social Sciences Foundation(Grant No.20BTQ065).
文摘(Aim)Chinese sign language is an essential tool for hearing-impaired to live,learn and communicate in deaf communities.Moreover,Chinese sign language plays a significant role in speech therapy and rehabilitation.Chinese sign language identification can provide convenience for those hearing impaired people and eliminate the communication barrier between the deaf community and the rest of society.Similar to the research of many biomedical image processing(such as automatic chest radiograph processing,diagnosis of chest radiological images,etc.),with the rapid development of artificial intelligence,especially deep learning technologies and algorithms,sign language image recognition ushered in the spring.This study aims to propose a novel sign language image recognition method based on an optimized convolutional neural network.(Method)Three different combinations of blocks:Conv-BN-ReLU-Pooling,Conv-BN-ReLU,Conv-BN-ReLU-BN were employed,including some advanced technologies such as batch normalization,dropout,and Leaky ReLU.We proposed an optimized convolutional neural network to identify 1320 sign language images,which was called as CNN-CB method.Totally ten runs were implemented with the hold-out randomly set for each run.(Results)The results indicate that our CNN-CB method gained an overall accuracy of 94.88±0.99%.(Conclusion)Our CNN-CB method is superior to thirteen state-of-the-art methods:eight traditional machine learning approaches and five modern convolutional neural network approaches.
基金This article is supported by the following projects:A Study on Individual Differences in Chinese Learning Needs and the Effect of Chinese Learning of International Students in Anhui Province(Grant No.SK2020A0034)A Study on the Effective Input and Output of Multimodal Synergy in College English Audio-video Classroom(Grant No.acjyyb2022078).
文摘Motivation is a key factor that influences the outcome of second language(L2)learning.Chinese as a second language(CSL)learners,however,may experience demotivation in their Chinese learning process which will,more often than not,reduce their learning interest and eventually affect their learning effect,therefore,it is necessary to enhance the learners’motivation level.This article first reviews the research literature in motivation in general,then discusses the CSL learners’demotivation in their Chinses learning process studying in China.Finally,it introduces motivational strategies to activate CSL learners’motivation in learning Chinese.
文摘This paper presents a systematic review of research on Chinese as a Second Language(CSL)education for ethnic minority students in Hong Kong SAR.Using three databases and screening with specific inclusion and exclusion criteria,the study selected 38 empirical studies published in English-language peer-reviewed journals.We find that there has been a surge of publications in Hong Kong in the past decade(2010–2020),and they are mostly authored by scholars from three universities in Hong Kong.Most of the research took a phenomenological approach,using interviews as the main data collection method and focusing on underprivileged South Asian students in secondary schools.The thematic analysis showed that Hong Kong’s CSL adopted a poststructuralist paradigm for understanding and revealing social inequalities surrounding Chinese language education for ethnic minority students.The study concludes that Hong Kong must decolonise its education system to genuinely support ethnic minority students to achieve educational equality and social justice.
文摘In this study, we made references to past literatures and developed an e-learning training program for CSL （Chinese as a Second Language） teachers. The class was held from July to August, 2010, in Chinese Culture University （Taiwan）, and we designed a performance-evaluation questionnaire with the Delphi method. Three months after the training program was completed, the questionnaire was given to the 30 students of the class, and they were asked to answer questions regarding their use of e-learning in the actual practice. We also asked 5 teachers to conduct experimental e-learning for us to video-record and observe. This effort allows us to discuss the use of e-learning among CSL teachers in Taiwan, come up with a conclusion and suggestions, and use the findings as references for course-planning and policies or research regarding the digital learning of Chinese.
