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The ZTSpeech System for CHiME-5 Challenge: A Far-field Speech Recognition System with Front-end and Robust Back-end
Li, Chenxing1,2; Wang Tieqiang1,2
2018-09
Conference NameCHiME 2018 Workshop on Speech Processing in Everyday Environments
Conference Date2018-9
Conference PlaceHyderabad, India
Abstract

In this paper, we describe our ZTSpeech for two tracks of CHiME-5 challenge. For front-end, our experiments conduct the comparisons between several popular beamforming methods. Besides, we also propose a omnidirectional minimum variance distortionless response (OMVDR) followed by weighted prediction error (WPE). Furthermore, we investigate the impact of data augmentation and data combinations.  For backend, several acoustic models (AMs) with different architectures are deeply investigated. N-gram-based and recurrent neural network (RNN)-based language models (LMs) are both evaluated. For single-array track, by combining the most effective approaches, our final system can achieve 11.94% promotion on performance in evaluation set, from 73.27% to 61.33%. For multiple-array track, our final system can achieve 12.29% improvement in evaluation set, from 73.30% to 61.01%.
 

Language英语
Document Type会议论文
Identifierhttp://ir.ia.ac.cn/handle/173211/39852
Collection数字内容技术与服务研究中心_智能技术与系统工程
Corresponding AuthorLi, Chenxing
Affiliation1.Institute of Automation, Chinese Academy of Sciences
2.University of Chinese Academy of Sciences
First Author AffilicationInstitute of Automation, Chinese Academy of Sciences
Corresponding Author AffilicationInstitute of Automation, Chinese Academy of Sciences
Recommended Citation
GB/T 7714
Li, Chenxing,Wang Tieqiang. The ZTSpeech System for CHiME-5 Challenge: A Far-field Speech Recognition System with Front-end and Robust Back-end[C],2018.
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