Paper
2 March 2022 The study of L2 mispronunciation detection based on Mandarin landmarks
Yanlu Xie, Man Li, Wenwei Dong
Author Affiliations +
Proceedings Volume 12158, International Conference on Computer Vision and Pattern Analysis (ICCPA 2021); 1215807 (2022) https://doi.org/10.1117/12.2626856
Event: 2021 International Conference on Computer Vision and Pattern Analysis, 2021, Guangzhou, China
Abstract
It has been proved that phonetics knowledge or data-driven method based acoustic landmarks are useful in detecting mispronunciation. The acoustic landmarks obtained by the two methods are not completely consistent. It shall be studied which method is better. The role that the acoustic landmarks play in the mispronunciation detection task needs to be further explored. This paper compared the consistency of different acoustic landmark detection methods. The paper also compared the effect of mispronunciation detection through TNDD-GOP architecture and hybrid CTC/Attention model. The paper verifies the role of acoustic landmark method in mispronunciation detection task with weighted method. The experimental results show that the higher the weight of acoustic landmark is added the better the detection performance is got. The results show that the mispronunciation detection performance of the updated acoustic landmark based on phonetics knowledge is better than that of the data-driven method. The DA and FRR are improved by 3.38% and 1.38%.
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Yanlu Xie, Man Li, and Wenwei Dong "The study of L2 mispronunciation detection based on Mandarin landmarks", Proc. SPIE 12158, International Conference on Computer Vision and Pattern Analysis (ICCPA 2021), 1215807 (2 March 2022); https://doi.org/10.1117/12.2626856
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KEYWORDS
Acoustics

Speech recognition

Data modeling

Performance modeling

Computer programming

Neural networks

Systems modeling

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