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混合CTC/attention架构端到端带口音普通话识别.
- Source :
-
Application Research of Computers / Jisuanji Yingyong Yanjiu . Mar2021, Vol. 38 Issue 3, p755-759. 5p. - Publication Year :
- 2021
-
Abstract
- To improve the performance of multi-accent Mandarin speech recognition task,this paper presented a method for hybrid end-to-end automatic speech recognition(ASR) by combining CTC and multi-head attention by using a multiobjective training and joint decoding.The analysis shows that hybrid model with lower CTC weight and deeper encoder layers performance better learning capacity.And it trained a very deep models with up to 48 layers for encode-decoder architecture,which outperforms all previous end-to-end ASR approaches on Aidatatang 200 h multi-accent dataset,achieves 5.6% character error rate(CER) and 26.2% sentence error rate(SER).The experiment proves that the recognition rate of the end-to-end model proposed exceeds the general end-to-end model,and it has certain advancedness in solving the Mandarin recognition with accents. [ABSTRACT FROM AUTHOR]
Details
- Language :
- Chinese
- ISSN :
- 10013695
- Volume :
- 38
- Issue :
- 3
- Database :
- Academic Search Index
- Journal :
- Application Research of Computers / Jisuanji Yingyong Yanjiu
- Publication Type :
- Academic Journal
- Accession number :
- 150438497
- Full Text :
- https://doi.org/10.19734/j.issn.1001-3695.2020.02.0036