Single Channel Speech Separation with Frame-based Summary Autocorrelation Function Analysis

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• 作者：E.R. Raghi^a ; ^{raghi.er@gmail.com" class="auth_mail" title="E-mail the corresponding author} ; M.S. Lekshmi^b
• 关键词：Summary autocorrelation function ; Modulation spectrum ; Periodicity detection
• 刊名：Procedia Technology
• 出版年：2016
• 出版时间：2016
• 年：2016
• 卷：24
• 期：Complete
• 页码：1074-1079
• 全文大小：83 K

文摘

Single channel speech separation system with frame based pitch range estimation is presented. The system decomposes the input mixture speech into frames and pitch of the speech is estimated in each frame of modulation spectrum by using summary autocorrelation function (SACF) analysis. In this method, each frame is divided into two, above and below 1 KHz and compute generalized autocorrelation for periodicity detection. By using this pitch range, a mask is created to filter the target speech from noisy mixture speech. Performance evaluation of the proposed system shows a better response compared to the existing methods.