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: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2020-01-01
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| Series: | Discrete Dynamics in Nature and Society |
| Online Access: | http://dx.doi.org/10.1155/2020/5476896 |
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| _version_ | 1850232592808280064 |
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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. |
| format | Article |
| id | doaj-art-0b060427e5a145778d232ea3315755d2 |
| institution | OA Journals |
| issn | 1026-0226 1607-887X |
| 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 |
| work_keys_str_mv | AT jianrongwang chinesetonerecognitionbasedon3ddynamicmuscleinformation AT liwan chinesetonerecognitionbasedon3ddynamicmuscleinformation AT juzhang chinesetonerecognitionbasedon3ddynamicmuscleinformation AT qiangfang chinesetonerecognitionbasedon3ddynamicmuscleinformation AT fanyang chinesetonerecognitionbasedon3ddynamicmuscleinformation AT jinghu chinesetonerecognitionbasedon3ddynamicmuscleinformation |