Assessing learners’ English public speaking anxiety with multimodal deep learning technologies-Reference-Cited by-同舟云学术

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Assessing learners’ English public speaking anxiety with multimodal deep learning technologies

Published:2024-05-11 Issue: Volume: Page:1-29
ISSN:0958-8221
Container-title:Computer Assisted Language Learning
language:en
Short-container-title:Computer Assisted Language Learning

Author:

Zheng Chunping¹^ORCID,Zhang Tingting²,Chen Xu¹,Zhang Huayang³,Wan Jiangbo⁴,Wu Bin²

Affiliation:

1. School of Humanities, Beijing University of Posts and Telecommunications, Beijing, China

2. Beijing Key Laboratory of Intelligent Telecommunication Software and Multimedia, School of Computer Science (National Pilot School of Software Engineering), Beijing University of Posts and Telecommunications, Beijing, China

3. School of Communication, Shenzhen Polytechnic University, Shenzhen, China

4. College of Foreign Languages and Literature, Fudan University, Shanghai, China

Funder

National Natural Science Foundation of China

Publisher

Informa UK Limited

Link

https://www.tandfonline.com/doi/pdf/10.1080/09588221.2024.2351129

Reference82 articles.

1. Researching feedback dialogue: an interactional analysis approach

2. The impact of automated writing evaluation (AWE) on EFL learners’ peer and self-editing

3. Baevski, A., Zhou, Y., Mohamed, A., & Auli, M. (2020). Wav2vec 2.0: A framework for self-supervised learning of speech representations [Paper presentation]. Proceedings of the 34th International Conference on Neural Information Processing Systems, Vancouver, BC, Canada, December 6-12.

4. Multimodal Machine Learning: A Survey and Taxonomy

5. Web-based language learning and speaking anxiety

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