{"title":"Speech enhancement using both spectral and spectral modulation domains","authors":"Julien Bosco, É. Plourde","doi":"10.1109/CCECE.2017.7946647","DOIUrl":null,"url":null,"abstract":"This paper proposes a speech enhancement approach that uses both the spectral and spectral modulation domains. In this approach, the noisy speech signal is enhanced simultaneously in the spectral domain, using a minimum mean square error (MMSE) short time spectral amplitude estimator, and in the spectral modulation domain, using a MMSE spectral modulation magnitude estimator. The results of both estimators are then weighted and combined together, using a function based on the a posteriori SNR, to produce the desired enhanced signal. Comparative results using both the segmental SNR and PESQ objective measures are presented for both stationary and non-stationary noises. It is observed that the proposed approach suppresses more noise than the compared approaches, but at the usual compromise of introducing speech distortions.","PeriodicalId":238720,"journal":{"name":"2017 IEEE 30th Canadian Conference on Electrical and Computer Engineering (CCECE)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 IEEE 30th Canadian Conference on Electrical and Computer Engineering (CCECE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CCECE.2017.7946647","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
This paper proposes a speech enhancement approach that uses both the spectral and spectral modulation domains. In this approach, the noisy speech signal is enhanced simultaneously in the spectral domain, using a minimum mean square error (MMSE) short time spectral amplitude estimator, and in the spectral modulation domain, using a MMSE spectral modulation magnitude estimator. The results of both estimators are then weighted and combined together, using a function based on the a posteriori SNR, to produce the desired enhanced signal. Comparative results using both the segmental SNR and PESQ objective measures are presented for both stationary and non-stationary noises. It is observed that the proposed approach suppresses more noise than the compared approaches, but at the usual compromise of introducing speech distortions.