SVIT‐SSR: A sEMG‐based vision transformer approach for silent speech recognition
Abstract Silent speech recognition (SSR) based on surface electromyography (sEMG) is a voice interaction technology proposed for scenarios requiring silent operations. This article abstracts the SSR task based on sEMG into a short‐term image sequence classification task. Time‐frequency domain featur...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2024-11-01
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| Series: | Electronics Letters |
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| Online Access: | https://doi.org/10.1049/ell2.13285 |
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| _version_ | 1850198632095023104 |
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| author | Zhao Li Bin Ma Weifan Mao Jianxing Zhang Zhuting Yu Yizhou Lu |
| author_facet | Zhao Li Bin Ma Weifan Mao Jianxing Zhang Zhuting Yu Yizhou Lu |
| author_sort | Zhao Li |
| collection | DOAJ |
| description | Abstract Silent speech recognition (SSR) based on surface electromyography (sEMG) is a voice interaction technology proposed for scenarios requiring silent operations. This article abstracts the SSR task based on sEMG into a short‐term image sequence classification task. Time‐frequency domain feature extraction and data reconstruction on the muscle activity segment data is performed. Additionally, the temporal and spatial dimensions to capture the intrinsic correlation representation of muscle activity is analysed. The SVIT‐SSR model is proposed based on the vision transformer (VIT) framework. Finally, experiments to identify 33 types of typical silent speech commands in the SSR dataset are designed. The results demonstrate that the proposed model achieves an accuracy of 96.67 ± 1.15%, outperforming similar algorithms. |
| format | Article |
| id | doaj-art-407142e260e049eeaed04dd46d7a0d51 |
| institution | OA Journals |
| issn | 0013-5194 1350-911X |
| language | English |
| publishDate | 2024-11-01 |
| publisher | Wiley |
| record_format | Article |
| series | Electronics Letters |
| spelling | doaj-art-407142e260e049eeaed04dd46d7a0d512025-08-20T02:12:49ZengWileyElectronics Letters0013-51941350-911X2024-11-016021n/an/a10.1049/ell2.13285SVIT‐SSR: A sEMG‐based vision transformer approach for silent speech recognitionZhao Li0Bin Ma1Weifan Mao2Jianxing Zhang3Zhuting Yu4Yizhou Lu5Shanghai Advanced Research Institute Chinese Academy of Sciences Shanghai ChinaShanghai Advanced Research Institute Chinese Academy of Sciences Shanghai ChinaShanghai Advanced Research Institute Chinese Academy of Sciences Shanghai ChinaShanghai Advanced Research Institute Chinese Academy of Sciences Shanghai ChinaShanghai Advanced Research Institute Chinese Academy of Sciences Shanghai ChinaShanghai Advanced Research Institute Chinese Academy of Sciences Shanghai ChinaAbstract Silent speech recognition (SSR) based on surface electromyography (sEMG) is a voice interaction technology proposed for scenarios requiring silent operations. This article abstracts the SSR task based on sEMG into a short‐term image sequence classification task. Time‐frequency domain feature extraction and data reconstruction on the muscle activity segment data is performed. Additionally, the temporal and spatial dimensions to capture the intrinsic correlation representation of muscle activity is analysed. The SVIT‐SSR model is proposed based on the vision transformer (VIT) framework. Finally, experiments to identify 33 types of typical silent speech commands in the SSR dataset are designed. The results demonstrate that the proposed model achieves an accuracy of 96.67 ± 1.15%, outperforming similar algorithms.https://doi.org/10.1049/ell2.13285electromyographyspeech recognition |
| spellingShingle | Zhao Li Bin Ma Weifan Mao Jianxing Zhang Zhuting Yu Yizhou Lu SVIT‐SSR: A sEMG‐based vision transformer approach for silent speech recognition Electronics Letters electromyography speech recognition |
| title | SVIT‐SSR: A sEMG‐based vision transformer approach for silent speech recognition |
| title_full | SVIT‐SSR: A sEMG‐based vision transformer approach for silent speech recognition |
| title_fullStr | SVIT‐SSR: A sEMG‐based vision transformer approach for silent speech recognition |
| title_full_unstemmed | SVIT‐SSR: A sEMG‐based vision transformer approach for silent speech recognition |
| title_short | SVIT‐SSR: A sEMG‐based vision transformer approach for silent speech recognition |
| title_sort | svit ssr a semg based vision transformer approach for silent speech recognition |
| topic | electromyography speech recognition |
| url | https://doi.org/10.1049/ell2.13285 |
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