M. Farhadloo, A. Sayadian, M. Asgari, A. Mostafavi
{"title":"语音增强的因果多分位数噪声谱估计","authors":"M. Farhadloo, A. Sayadian, M. Asgari, A. Mostafavi","doi":"10.1109/ATNAC.2008.4783306","DOIUrl":null,"url":null,"abstract":"Suppression of additive noise from speech signal is a fundamental problem in audio signal processing. We present in this paper a novel algorithm for single channel speech enhancement. The algorithm consists of two steps: First, estimation of the noise power spectrum with a multi quantile method and second, elimination of the estimated noise from the observed signal by spectral subtraction or Wiener filtering. In this method, instead of a global quantile for all frequency bands, we divide the entire frequency band into three regions and use different quantile in each region. Our simulation results show that the new method has better performance than quantile based noise estimation.","PeriodicalId":143803,"journal":{"name":"2008 Australasian Telecommunication Networks and Applications Conference","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2008-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Causal Multi Quantile Noise Spectrum Estimation for Speech Enhancement\",\"authors\":\"M. Farhadloo, A. Sayadian, M. Asgari, A. Mostafavi\",\"doi\":\"10.1109/ATNAC.2008.4783306\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Suppression of additive noise from speech signal is a fundamental problem in audio signal processing. We present in this paper a novel algorithm for single channel speech enhancement. The algorithm consists of two steps: First, estimation of the noise power spectrum with a multi quantile method and second, elimination of the estimated noise from the observed signal by spectral subtraction or Wiener filtering. In this method, instead of a global quantile for all frequency bands, we divide the entire frequency band into three regions and use different quantile in each region. Our simulation results show that the new method has better performance than quantile based noise estimation.\",\"PeriodicalId\":143803,\"journal\":{\"name\":\"2008 Australasian Telecommunication Networks and Applications Conference\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2008-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2008 Australasian Telecommunication Networks and Applications Conference\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ATNAC.2008.4783306\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2008 Australasian Telecommunication Networks and Applications Conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ATNAC.2008.4783306","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Causal Multi Quantile Noise Spectrum Estimation for Speech Enhancement
Suppression of additive noise from speech signal is a fundamental problem in audio signal processing. We present in this paper a novel algorithm for single channel speech enhancement. The algorithm consists of two steps: First, estimation of the noise power spectrum with a multi quantile method and second, elimination of the estimated noise from the observed signal by spectral subtraction or Wiener filtering. In this method, instead of a global quantile for all frequency bands, we divide the entire frequency band into three regions and use different quantile in each region. Our simulation results show that the new method has better performance than quantile based noise estimation.