{"id":158122,"date":"2009-08-24T00:00:00","date_gmt":"2009-08-24T00:00:00","guid":{"rendered":"https:\/\/www.microsoft.com\/en-us\/research\/msr-research-item\/unified-framework-for-single-channel-speech-enhancement\/"},"modified":"2020-06-04T15:05:06","modified_gmt":"2020-06-04T22:05:06","slug":"unified-framework-for-single-channel-speech-enhancement","status":"publish","type":"msr-research-item","link":"https:\/\/www.microsoft.com\/en-us\/research\/publication\/unified-framework-for-single-channel-speech-enhancement\/","title":{"rendered":"Unified Framework for Single Channel Speech Enhancement"},"content":{"rendered":"<div class=\"asset-content\">\n<p>In this paper we describe a generic architecture for single channel speech enhancement. We assume processing in frequency domain and suppression based speech enhancement methods. The framework consists of a two stage voice activity detector, noise variance estimator, a suppression rule, and an uncertain presence of the speech signal modifier. The evaluation corpus is a synthetic mixture of a clean speech (TIMIT database) and in-car recorded noises. Using the framework multiple speech enhancement algorithms are tuned for maximum performance. We propose a formalized procedure for automated tuning of these algorithms. The optimization criterion is a weighted sum of the mean opinion score (PESQ-MOS), signalto-noise-ratio (SNR), log-spectral distance (LSD), and mean square error (MSE). The proposed framework provides a complete speech enhancement chain and can be used for evaluation and tuning of other suppression rules and voice activity detector algorithms.<\/p>\n<\/div>\n<p><!-- .asset-content --><\/p>\n","protected":false},"excerpt":{"rendered":"<p>In this paper we describe a generic architecture for single channel speech enhancement. We assume processing in frequency domain and suppression based speech enhancement methods. The framework consists of a two stage voice activity detector, noise variance estimator, a suppression rule, and an uncertain presence of the speech signal modifier. The evaluation corpus is a 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