{"title":"音频背景噪声降噪的频域多通道期望最大化算法","authors":"Jichi Deng, S. Godsill","doi":"10.1109/WASPAA.2013.6701859","DOIUrl":null,"url":null,"abstract":"In this paper we implement expectation maximization (EM) based methods in the short time Fourier transform (STFT) domain for background noise reduction in multi-channel systems. The models introduce a Wishart prior for the unknown signal covariance matrix. An EM algorithm is used to maximise the posterior probability for the clean signal, approaching a stationary point of the distribution with increasing iterations. The background noise is modelled as white and stationary in this initial work. The proposed methods are found to outperform a multi-channel Wiener filter in terms of residual noise artefacts and MSE for a small initial trial.","PeriodicalId":341888,"journal":{"name":"2013 IEEE Workshop on Applications of Signal Processing to Audio and Acoustics","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Frequency domain multi-channel expectation maximization algorithm for audio background noise reduction\",\"authors\":\"Jichi Deng, S. Godsill\",\"doi\":\"10.1109/WASPAA.2013.6701859\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper we implement expectation maximization (EM) based methods in the short time Fourier transform (STFT) domain for background noise reduction in multi-channel systems. The models introduce a Wishart prior for the unknown signal covariance matrix. An EM algorithm is used to maximise the posterior probability for the clean signal, approaching a stationary point of the distribution with increasing iterations. The background noise is modelled as white and stationary in this initial work. The proposed methods are found to outperform a multi-channel Wiener filter in terms of residual noise artefacts and MSE for a small initial trial.\",\"PeriodicalId\":341888,\"journal\":{\"name\":\"2013 IEEE Workshop on Applications of Signal Processing to Audio and Acoustics\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2013 IEEE Workshop on Applications of Signal Processing to Audio and Acoustics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/WASPAA.2013.6701859\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 IEEE Workshop on Applications of Signal Processing to Audio and Acoustics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/WASPAA.2013.6701859","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Frequency domain multi-channel expectation maximization algorithm for audio background noise reduction
In this paper we implement expectation maximization (EM) based methods in the short time Fourier transform (STFT) domain for background noise reduction in multi-channel systems. The models introduce a Wishart prior for the unknown signal covariance matrix. An EM algorithm is used to maximise the posterior probability for the clean signal, approaching a stationary point of the distribution with increasing iterations. The background noise is modelled as white and stationary in this initial work. The proposed methods are found to outperform a multi-channel Wiener filter in terms of residual noise artefacts and MSE for a small initial trial.
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