Algorithm Research & Explore
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App. Res. of Comp. Printed Article
Vol. 38, 2021 No. 3
755-759

Hybrid CTC/attention architecture for end-to-end multi-accent Mandarin speech recognition

Yang Wei
Hu Yan
School of Computer Science & Technology, Wuhan University of Technology, Wuhan 430000, China
DOI: 10.19734/j.issn.1001-3695.2020.02.0036

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.

Foundation Support

湖北省自然科学基金资助项目(2019CFC919)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2020.02.0036
Publish at: Application Research of Computers Printed Article, Vol. 38, 2021 No. 3
Section: Algorithm Research & Explore
Pages: 755-759
Serial Number: 1001-3695(2021)03-022-0755-05

Publish History

[2021-03-05] Printed Article

Cite This Article

杨威, 胡燕. 混合CTC/attention架构端到端带口音普通话识别 [J]. 计算机应用研究, 2021, 38 (3): 755-759. (Yang Wei, Hu Yan. Hybrid CTC/attention architecture for end-to-end multi-accent Mandarin speech recognition [J]. Application Research of Computers, 2021, 38 (3): 755-759. )

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  • Application Research of Computers Monthly Journal
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Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

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