3M: An Effective Multi-view, Multi-granularity, and Multi-aspect Modeling Approach to English Pronunciation Assessment-Reference-Cited by-同舟云学术

3M: An Effective Multi-view, Multi-granularity, and Multi-aspect Modeling Approach to English Pronunciation Assessment

Published:2022-11-07 Issue: Volume: Page:
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Container-title:2022 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC)
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Author:

Chao Fu-An¹,Lo Tien-Hong¹,Wu Tzu-I²,Sung Yao-Ting³,Chen Berlin²

Affiliation:

1. Research Center for Psychological and Educational Testing, National Taiwan Normal University,Taiwan

2. National Taiwan Normal University,Department of Computer Science and Information Engineering,Taiwan

3. National Taiwan Normal University,Department of Educational Psychology and Counseling,Taiwan

Publisher

IEEE

Link

Reference35 articles.

1. WavLM: Large-scale self-supervised pretraining for full stack speech processing;chen;ArXiv Preprint,2021

3. Improving perceptual quality by phone-fortified perceptual loss for speech enhancement;hsieh;ArXiv Preprint,2020

4. wav2vec 2.0: A framework for self-supervised learning of speech representations;baevski;ArXiv Preprint,2020

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