Towards Robust Mispronunciation Detection and Diagnosis for L2 English Learners with Accent-Modulating Methods

Shao Wei Fan Jiang, Bi Cheng Yan, Tien Hong Lo, Fu An Chao, Berlin Chen

研究成果: 書貢獻/報告類型會議論文篇章

3 引文 斯高帕斯(Scopus)

摘要

With the acceleration of globalization, more and more people are willing or required to learn second languages (L2). One of the major remaining challenges facing current mispronunciation and diagnosis (MDD) models for use in computer-assisted pronunciation training (CAPT) is to handle speech from L2 learners with a diverse set of accents. In this paper, we set out to mitigate the adverse effects of accent variety in building an L2 English MDD system with end-to-end (E2E) neural models. To this end, we first propose an effective modeling framework that infuses accent features into an E2E MDD model, thereby making the model more accent-aware. Going a step further, we design and present disparate accent-aware modules to perform accent-aware modulation of acoustic features in a finer-grained manner, so as to enhance the discriminating capability of the resulting MDD model. Extensive sets of experiments conducted on the L2-ARCTIC benchmark dataset show the merits of our MDD model, in comparison to some existing E2E-based strong baselines and the celebrated pronunciation scoring based method.

原文英語
主出版物標題2021 IEEE Automatic Speech Recognition and Understanding Workshop, ASRU 2021 - Proceedings
發行者Institute of Electrical and Electronics Engineers Inc.
頁面1065-1070
頁數6
ISBN(電子)9781665437394
DOIs
出版狀態已發佈 - 2021
事件2021 IEEE Automatic Speech Recognition and Understanding Workshop, ASRU 2021 - Cartagena, 哥伦比亚
持續時間: 2021 12月 132021 12月 17

出版系列

名字2021 IEEE Automatic Speech Recognition and Understanding Workshop, ASRU 2021 - Proceedings

會議

會議2021 IEEE Automatic Speech Recognition and Understanding Workshop, ASRU 2021
國家/地區哥伦比亚
城市Cartagena
期間2021/12/132021/12/17

ASJC Scopus subject areas

  • 電腦視覺和模式識別
  • 訊號處理
  • 語言和語言學

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