Chinese Tone Recognition Based on 3D Dynamic Muscle Information

To advance the study of lip-reading recognition in accordance with Chinese pronunciation norms, we carefully investigated Mandarin tone recognition based on visual information, in contrast to that of the previous character-based Chinese lip reading technique. In this paper, we mainly studied the vow...

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Main Authors: JianRong Wang, Li Wan, Ju Zhang, Qiang Fang, Fan Yang, Jing Hu
Format: Article
Language:English
Published: Wiley 2020-01-01
Series:Discrete Dynamics in Nature and Society
Online Access:http://dx.doi.org/10.1155/2020/5476896
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author JianRong Wang
Li Wan
Ju Zhang
Qiang Fang
Fan Yang
Jing Hu
author_facet JianRong Wang
Li Wan
Ju Zhang
Qiang Fang
Fan Yang
Jing Hu
author_sort JianRong Wang
collection DOAJ
description To advance the study of lip-reading recognition in accordance with Chinese pronunciation norms, we carefully investigated Mandarin tone recognition based on visual information, in contrast to that of the previous character-based Chinese lip reading technique. In this paper, we mainly studied the vowel tonal transformation in Chinese pronunciation and designed a lightweight skipping convolution network framework (SCNet). And, the experimental results showed that the SCNet was sensitive to the more detailed description of the pitch change than that of the traditional model and achieved a better tone recognition effect and outstanding antiinterference performance. In addition, we conducted a more detailed study on the assistance of the deep texture information in lip-reading recognition. We found that the deep texture information has a significant effect on tone recognition, and the possibility of multimodal lip reading in Chinese tone recognition was confirmed. Similarly, we verified the role of the SCNet syllable tone recognition and found that the vowel and syllable tone recognition accuracy of our model was as high as 97.3%, which also showed the robustness of our proposed method for Chinese tone recognition and it can be widely used for tone recognition.
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institution OA Journals
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language English
publishDate 2020-01-01
publisher Wiley
record_format Article
series Discrete Dynamics in Nature and Society
spelling doaj-art-0b060427e5a145778d232ea3315755d22025-08-20T02:03:08ZengWileyDiscrete Dynamics in Nature and Society1026-02261607-887X2020-01-01202010.1155/2020/54768965476896Chinese Tone Recognition Based on 3D Dynamic Muscle InformationJianRong Wang0Li Wan1Ju Zhang2Qiang Fang3Fan Yang4Jing Hu5College of Intelligence and Computing, Tianjin University, Tianjin 300350, ChinaCollege of Intelligence and Computing, Tianjin University, Tianjin 300350, ChinaCollege of Intelligence and Computing, Tianjin University, Tianjin 300350, ChinaInstitute of Linguistics, Chinese Academy of Social Sciences, Beijing 100732, ChinaCollege of Intelligence and Computing, Tianjin University, Tianjin 300350, ChinaCollege of Intelligence and Computing, Tianjin University, Tianjin 300350, ChinaTo advance the study of lip-reading recognition in accordance with Chinese pronunciation norms, we carefully investigated Mandarin tone recognition based on visual information, in contrast to that of the previous character-based Chinese lip reading technique. In this paper, we mainly studied the vowel tonal transformation in Chinese pronunciation and designed a lightweight skipping convolution network framework (SCNet). And, the experimental results showed that the SCNet was sensitive to the more detailed description of the pitch change than that of the traditional model and achieved a better tone recognition effect and outstanding antiinterference performance. In addition, we conducted a more detailed study on the assistance of the deep texture information in lip-reading recognition. We found that the deep texture information has a significant effect on tone recognition, and the possibility of multimodal lip reading in Chinese tone recognition was confirmed. Similarly, we verified the role of the SCNet syllable tone recognition and found that the vowel and syllable tone recognition accuracy of our model was as high as 97.3%, which also showed the robustness of our proposed method for Chinese tone recognition and it can be widely used for tone recognition.http://dx.doi.org/10.1155/2020/5476896
spellingShingle JianRong Wang
Li Wan
Ju Zhang
Qiang Fang
Fan Yang
Jing Hu
Chinese Tone Recognition Based on 3D Dynamic Muscle Information
Discrete Dynamics in Nature and Society
title Chinese Tone Recognition Based on 3D Dynamic Muscle Information
title_full Chinese Tone Recognition Based on 3D Dynamic Muscle Information
title_fullStr Chinese Tone Recognition Based on 3D Dynamic Muscle Information
title_full_unstemmed Chinese Tone Recognition Based on 3D Dynamic Muscle Information
title_short Chinese Tone Recognition Based on 3D Dynamic Muscle Information
title_sort chinese tone recognition based on 3d dynamic muscle information
url http://dx.doi.org/10.1155/2020/5476896
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AT qiangfang chinesetonerecognitionbasedon3ddynamicmuscleinformation
AT fanyang chinesetonerecognitionbasedon3ddynamicmuscleinformation
AT jinghu chinesetonerecognitionbasedon3ddynamicmuscleinformation