The preliminary study of robust speech feature extraction based on maximizing the accuracy of states in deep acoustic models

Li-chia Chang, Jeih-weih Hung


Anthology ID:
2020.rocling-1.14
Volume:
Proceedings of the 32nd Conference on Computational Linguistics and Speech Processing (ROCLING 2020)
Month:
September
Year:
2020
Address:
Taipei, Taiwan
Venue:
ROCLING
SIG:
Publisher:
The Association for Computational Linguistics and Chinese Language Processing (ACLCLP)
Note:
Pages:
118–119
Language:
URL:
https://aclanthology.org/2020.rocling-1.14
DOI:
Bibkey:
Cite (ACL):
Li-chia Chang and Jeih-weih Hung. 2020. The preliminary study of robust speech feature extraction based on maximizing the accuracy of states in deep acoustic models. In Proceedings of the 32nd Conference on Computational Linguistics and Speech Processing (ROCLING 2020), pages 118–119, Taipei, Taiwan. The Association for Computational Linguistics and Chinese Language Processing (ACLCLP).
Cite (Informal):
The preliminary study of robust speech feature extraction based on maximizing the accuracy of states in deep acoustic models (Chang & Hung, ROCLING 2020)
Copy Citation:
PDF:
https://aclanthology.org/2020.rocling-1.14.pdf