Speech Enhancement Algorithm of Binary Mask Estimation Based on a Priori SNR Constraints

Jie Wang, Chengcheng Yang, Linhuang Yan, Manlu Huang, Jinqiu Sang

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations

Abstract

A speech enhancement algorithm using binary mask estimation and a priori SNR constraints is proposed. The a priori SNR estimation has a major impact on noise spectrum estimation function, so the MMSE rule is used to modify the a priori SNR through secondary processing to get more accurate estimated noise power spectrum and gain function, which are used to retain noise over-estimated Time-Frequency units and discard noise under-estimated Time-Frequency units. Experiments results show that the proposed algorithm can improve the intelligibility of speech signals for low SNR.

Original languageEnglish
Title of host publication2018 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2018 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages937-943
Number of pages7
ISBN (Electronic)9789881476852
DOIs
StatePublished - 2 Jul 2018
Externally publishedYes
Event10th Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2018 - Honolulu, United States
Duration: 12 Nov 201815 Nov 2018

Publication series

Name2018 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2018 - Proceedings

Conference

Conference10th Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2018
Country/TerritoryUnited States
CityHonolulu
Period12/11/1815/11/18

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