Post-filtering technique using band importance function for speech intelligibility enhancement

Ying Hui Lai, Shih Tsang Tang, Pei Chun Li

研究成果: Conference contribution同行評審

1 引文 斯高帕斯(Scopus)

摘要

Conventional speech enhancement (SE) algorithms are mainly designed with the aim of improving signal-to-noise levels of noisy speech signals. However, many applications consider the enhancement of speech intelligibility as the goal for an SE system. In this study, we propose a maximum speech intelligibility (MSI) post-filter that aims to enhance the intelligibility of processed speech signals. The MSI post-filter is designed to specify a weight for each frequency band of the speech signal based on the critical band importance function. To evaluate the MSI post-filter, we combine it with a recently proposed generalized maximum a posteriori spectral amplitude estimation (GMAPA) SE algorithm. In previous studies, it has been verified that GMAPA outperforms several well-known spectral restoration approaches in terms of objective evaluations and speech recognition tests. Experimental results from the present study confirm that GMAPA also provides better results in a set of subjective intelligibility tests conducted with human subjects. Moreover, the integration of GMAPA and MSI can further improve the intelligibility scores over GMAPA alone under - 10 dB to 5 dB signal-to-noise ratio conditions.

原文English
主出版物標題Proceedings - 2016 IEEE 2nd International Conference on Multimedia Big Data, BigMM 2016
發行者Institute of Electrical and Electronics Engineers Inc.
頁面487-491
頁數5
ISBN(電子)9781509021789
DOIs
出版狀態Published - 16 8月 2016
事件2nd IEEE International Conference on Multimedia Big Data, BigMM 2016 - Taipei, Taiwan
持續時間: 20 4月 201622 4月 2016

出版系列

名字Proceedings - 2016 IEEE 2nd International Conference on Multimedia Big Data, BigMM 2016

Conference

Conference2nd IEEE International Conference on Multimedia Big Data, BigMM 2016
國家/地區Taiwan
城市Taipei
期間20/04/1622/04/16

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