CDSD: Chinese Dysarthria Speech Database
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arXiv
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| Autori principali: | , , , , , , |
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| Natura: | Preprint |
| Pubblicazione: |
2023
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| _version_ | 1866915149808402432 |
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| author | Wang, Yan Sun, Mengyi Kang, Xinchen Li, Jingting Guo, Pengfei Gao, Ming Wang, Su-Jing |
| author_facet | Wang, Yan Sun, Mengyi Kang, Xinchen Li, Jingting Guo, Pengfei Gao, Ming Wang, Su-Jing |
| contents | Dysarthric speech poses significant challenges for individuals with dysarthria, impacting their ability to communicate socially. Despite the widespread use of Automatic Speech Recognition (ASR), accurately recognizing dysarthric speech remains a formidable task, largely due to the limited availability of dysarthric speech data. To address this gap, we developed the Chinese Dysarthria Speech Database (CDSD), the most extensive collection of Chinese dysarthria data to date, featuring 133 hours of recordings from 44 speakers. Our benchmarks reveal a best Character Error Rate (CER) of 16.4\%. Compared to the CER of 20.45\% from our additional human experiments, Dysarthric Speech Recognition (DSR) demonstrates its potential in significant improvement of communication for individuals with dysarthria. The CDSD database will be made publicly available at http://melab.psych.ac.cn/CDSD.html. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2310_15930 |
| institution | arXiv |
| publishDate | 2023 |
| record_format | arxiv |
| spellingShingle | CDSD: Chinese Dysarthria Speech Database Wang, Yan Sun, Mengyi Kang, Xinchen Li, Jingting Guo, Pengfei Gao, Ming Wang, Su-Jing Sound Audio and Speech Processing Dysarthric speech poses significant challenges for individuals with dysarthria, impacting their ability to communicate socially. Despite the widespread use of Automatic Speech Recognition (ASR), accurately recognizing dysarthric speech remains a formidable task, largely due to the limited availability of dysarthric speech data. To address this gap, we developed the Chinese Dysarthria Speech Database (CDSD), the most extensive collection of Chinese dysarthria data to date, featuring 133 hours of recordings from 44 speakers. Our benchmarks reveal a best Character Error Rate (CER) of 16.4\%. Compared to the CER of 20.45\% from our additional human experiments, Dysarthric Speech Recognition (DSR) demonstrates its potential in significant improvement of communication for individuals with dysarthria. The CDSD database will be made publicly available at http://melab.psych.ac.cn/CDSD.html. |
| title | CDSD: Chinese Dysarthria Speech Database |
| topic | Sound Audio and Speech Processing |
| url | https://arxiv.org/abs/2310.15930 |