Mobile-assisted pronunciation learning with feedback from peers and/or automatic speech recognition: a mixed-methods study-Reference-Cited by-同舟云学术

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Mobile-assisted pronunciation learning with feedback from peers and/or automatic speech recognition: a mixed-methods study

Published:2021-07-26 Issue: Volume: Page:1-24
ISSN:0958-8221
Container-title:Computer Assisted Language Learning
language:en
Short-container-title:Computer Assisted Language Learning

Author:

Dai Yuanjun¹²,Wu Zhiwei³

Affiliation:

1. Department of Humanities and Social Sciences, Xinghai Conservatory of Music, Guangzhou, China

2. College of Foreign Studies, Jinan University, Guangzhou, China

3. Department of Chinese and Bilingual Studies, The Hong Kong Polytechnic University, Hong Kong, China

Funder

China Postdoctoral Science Foundation

Publisher

Informa UK Limited

Subject

Computer Science Applications,Linguistics and Language,Language and Linguistics

Link

https://www.tandfonline.com/doi/pdf/10.1080/09588221.2021.1952272

Reference42 articles.

1. Web-based language learning and speaking anxiety

2. Learner affect in computerised L2 oral grammar practice with corrective feedback

3. A longitudinal case study of changes in students’ attitudes, participation, and learning in collaborative writing

4. A Study of web-based oral activities enhanced by Automatic Speech Recognition for EFL college learning

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1. The effectiveness of L2 pronunciation instruction: A critical systematic review of the intervention studies;The Literacy Trek;2024-06-30

2. The Impact of Visual Corrective Feedback on Pronunciation Accuracy in L2 Sound Production;Advances in Educational Technologies and Instructional Design;2024-05-10

3. Design of Intelligent Speech Recognition System Based on Data Analysis Algorithm;2024 IEEE 13th International Conference on Communication Systems and Network Technologies (CSNT);2024-04-06

4. Fostering L2 Learners’ Pronunciation and Motivation via Affordances of Artificial Intelligence;Computers in the Schools;2024-04-05

5. Aggregating the evidence of automatic speech recognition research claims in CALL;System;2024-04

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