PTeacher: a Computer-Aided Personalized Pronunciation Training System with Exaggerated Audio-Visual Corrective Feedback

要旨

Second language (L2) English learners often find it difficult to improve their pronunciations due to the lack of expressive and personalized corrective feedback. In this paper, we present Pronunciation Teacher—PTeacher, a Computer-Aided Pronunciation Training (CAPT) system that provides personalized exaggerated audio-visual corrective feedback for mispronunciations. Though the effectiveness of exaggerated feedback has been demonstrated, it is still unclear how to define the appropriate degrees of exaggeration when interacting with individual learners. To fill in this gap, we interview 100 L2 English learners and 22 professional native teachers to understand their needs and experiences. Three critical metrics are proposed for both learners and teachers to identify the best exaggeration levels in both audio and visual modalities. Additionally, we incorporate the personalized dynamic feedback mechanism given the English proficiency of learners. Based on the obtained insights, a comprehensive interactive pronunciation training course is designed to help L2 learners rectify mispronunciations in a more perceptible, understandable, and discriminative manner. Extensive user studies demonstrate that our system significantly promotes the learners' learning efficiency.

著者
Yaohua Bu
Tsinghua University, Beijing, China
Tianyi Ma
Tsinghua University, Beijing, China
Weijun Li
Northeast Normal University, Beijing, China
Hang Zhou
The Chinese University of Hong Kong, Hong Kong, China
Jia Jia
Tsinghua University, Beijing, China
Shengqi Chen
Tsinghua University, Beijing, China
Kaiyuan Xu
Tsinghua University, Beijing, China
Dachuan Shi
Tsinghua University, Beijing, China
Haozhe Wu
Tsinghua University, Beijing, China
Zhihan Yang
Tsinghua University, Beijing, China
Kun Li
Speech X Limited, Beijing, China
Zhiyong Wu
Tsinghua University, Beijing, China
Yuanchun Shi
Tsinghua University, Beijing, China
Xiaobo Lu
Tsinghua University, Beijing, China
Ziwei Liu
The Chinese University of Hong Kong, Hong Kong, China
DOI

10.1145/3411764.3445490

論文URL

https://doi.org/10.1145/3411764.3445490

動画

会議: CHI 2021

The ACM CHI Conference on Human Factors in Computing Systems (https://chi2021.acm.org/)

セッション: Systems for Learning

[A] Paper Room 11, 2021-05-12 17:00:00~2021-05-12 19:00:00 / [B] Paper Room 11, 2021-05-13 01:00:00~2021-05-13 03:00:00 / [C] Paper Room 11, 2021-05-13 09:00:00~2021-05-13 11:00:00
Paper Room 11
11 件の発表
2021-05-12 17:00:00
2021-05-12 19:00:00
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