Zobrazeno 1 - 4
of 4
pro vyhledávání: '"Hsiu-Wei Yeh"'
Autor:
Hsiu-Wei Yeh, 葉修瑋
106
Dysarthria speech is ambiguous because of the interference between the brain's nerve signals and the muscles of the vocal organs, making it difficult for patients to communicate smoothly. Nowadays, the most common clinical treatment method i
Dysarthria speech is ambiguous because of the interference between the brain's nerve signals and the muscles of the vocal organs, making it difficult for patients to communicate smoothly. Nowadays, the most common clinical treatment method i
Externí odkaz:
http://ndltd.ncl.edu.tw/handle/m6538d
Autor:
Hsiu-wei Yeh, 葉秀薇
91
Design collaboration between industry and university is an important gateway to the development of new product concepts, not only to satisfy industry’s need for innovation, but also to integrate resources between industry and university in
Design collaboration between industry and university is an important gateway to the development of new product concepts, not only to satisfy industry’s need for innovation, but also to integrate resources between industry and university in
Externí odkaz:
http://ndltd.ncl.edu.tw/handle/83815175531025429468
Autor:
Syu-Siang, Wang, Yu, Tsao, Wei-Zhong, Zheng, Hsiu-Wei, Yeh, Pei-Chun, Li, Shih-Hau, Fang, Ying-Hui, Lai
Publikováno v:
2022 44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC).
Generally, those patients with dysarthria utter a distorted sound and the restrained intelligibility of a speech for both human and machine. To enhance the intelligibility of dysarthric speech, we applied a deep learning-based speech enhancement (SE)
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e9ccc4a15a030f6227f5a27a942f52e3
https://doi.org/10.1109/embc48229.2022.9871531
https://doi.org/10.1109/embc48229.2022.9871531
Publikováno v:
EMBC
Dysarthria speakers suffer from poor communication, and voice conversion (VC) technology is a potential approach for improving their speech quality. This study presents a joint feature learning approach to improve a sub-band deep neural network-based
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1eb056541ff874b0d07a79ca54de25d2
https://doi.org/10.1109/embc.2019.8856560
https://doi.org/10.1109/embc.2019.8856560