{"title":"语音增强使用频谱和频谱调制域","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":"{\"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}","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}
Speech enhancement using both spectral and spectral modulation domains
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.