A systematic literature review of research on automatic speech recognition in EFL pronunciation

被引:1
作者
Liu, Yao [1 ,2 ]
Ab Rahman, Faizahani Binti [1 ]
Zain, Farah Binti Mohamad [1 ]
机构
[1] Univ Utara Malaysia, Sch Educ, Sintok, Kedah Darul Ama, Malaysia
[2] Shandong Womens Univ, Sch Foreign Languages, Jinan, Shandong, Peoples R China
关键词
Automatic speech recognition; EFL; pronunciation; systematic literature review; ENGLISH PRONUNCIATION; CORRECTIVE FEEDBACK; ASR; LEARNERS; TECHNOLOGY; INSTRUCTION;
D O I
10.1080/2331186X.2025.2466288
中图分类号
G40 [教育学];
学科分类号
040101 ; 120403 ;
摘要
To help EFL learners improve English pronunciation skills, researchers have recently turned to automatic speech recognition (ASR) technology. Despite some attempted review studies, relatively few have targeted ASR in an EFL setting. Therefore, the current study aims to delve into various aspects of ASR implementation, including theoretical foundations, research topics, research methods, target features, measurements, and findings, drawing upon published empirical literature. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses guided the review. Of the 6138 articles with 2886 from Web of Science Core Collection and 3252 from Scopus, a total of 24 empirical articles were included. The results revealed: (1) twenty percent of the studies consisted of underpinning theories/models/concepts for the implementation of ASR in an EFL context; (2) a majority of studies adopted a quasi-experimental design, primarily focusing on the pronunciation gains in accuracy; (3) most learning activities with the use of ASR tools were designed for in-class activities; (4) the reviewed ASR studies were primarily concerned with the production accuracy of segmental features. Based on the findings, ASR is proven to be an effective tool in language classrooms but entails limitations. Future studies should investigate how ASR can best be implemented in a classroom setting.
引用
收藏
页数:15
相关论文
共 84 条
[31]   Utilizing robot-tutoring approach in oral reading to improve Taiwanese EFL students' English pronunciation [J].
Hong, Zeng-Wei ;
Tsai, Ming-Hsiu Michelle ;
Ku, Chin Soon ;
Cheng, Wai Khuen ;
Chen, Jian-Tan ;
Lin, Jim-Min .
COGENT EDUCATION, 2024, 11 (01)
[32]   An Examination of Automatic Speech Recognition (ASR)-based Computer-assisted Pronunciation Training (CAPT) for Less-proficient EFL Students Using the Technology Acceptance Model [J].
Hsu, Hsiao-Wen .
INTERNATIONAL JOURNAL OF TECHNOLOGY IN EDUCATION, 2024, 7 (03) :456-473
[34]   Effectiveness of interventions on improving English language learners' intelligibility and comprehensibility: A meta-analytic review [J].
Hu, Xueyan ;
Kuo, Li-Jen ;
Dixon, L. Quentin .
LANGUAGE TEACHING RESEARCH, 2022, :2046-2070
[35]   Systematic survey of anything-to-text recognition and constructing its framework in language learning [J].
Hwang, Wu-Yuin ;
Nguyen, Van-Giap ;
Purba, Siska Wati Dewi .
EDUCATION AND INFORMATION TECHNOLOGIES, 2022, 27 (09) :12273-12299
[36]   Implementing IT Service Management: A systematic literature review [J].
Iden, Jon ;
Roar Eikebrokk, Tom .
INTERNATIONAL JOURNAL OF INFORMATION MANAGEMENT, 2013, 33 (03) :512-523
[37]   Assessment of L2 intelligibility: Comparing L1 listeners and automatic speech recognition [J].
Inceoglu, Solene ;
Chen, Wen-Hsin ;
Lim, Hyojung .
RECALL, 2023, 35 (01) :89-104
[38]   ASR for EFL Pronunciation Practice: Segmental Development and Learners' Beliefs [J].
Inceoglu, Solene ;
Lim, Hyojung ;
Chen, Wen-Hsin .
JOURNAL OF ASIA TEFL, 2020, 17 (03) :824-840
[39]  
Jenkins J., 2000, PHONOLOGY ENGLISH IN
[40]   Effects of Automatic Speech Recognition Technology on EFL Learners' Willingness to Communicate and Interactional Features [J].
Jiang, Michael Yi-Chao ;
Jong, Morris Siu-Yung ;
Lau, Wilfred Wing -Fat ;
Chai, Ching -Sing ;
Wu, Na .
EDUCATIONAL TECHNOLOGY & SOCIETY, 2023, 26 (03) :37-52