Structured mean field method for single-microphone speech separation with factorial Hidden Markov Model
Refereed conference paper presented and published in conference proceedings

香港中文大學研究人員
替代計量分析
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其它資訊
摘要A variational statistical inference method referred as structured mean field method is studied for factorial Hidden Markov Model (HMM) formulation of single-microphone speech separation problem. By decoupling the Markov chains of the individual speech sources coupled during the mixing process of the speech mixture, the complexity of temporal inference of the speech sources is reduced to quadratic with the number of acoustic states of the sources. Speech separation and automatic speech recognition experiments are performed on the reconstructed speech. Experimental results show that the studied approximating inference method achieves the similar separation results as the exact inference algorithm in terms of Perceptual Evaluation of Speech Quality (PESQ) and word error rate (WER). © 2013 IEEE.
著者Yeung Y.T., Lee T.
會議名稱2013 IEEE China Summit and International Conference on Signal and Information Processing, ChinaSIP 2013
會議開始日06.07.2013
會議完結日10.07.2013
會議地點Beijing
會議國家/地區中國
詳細描述organized by IEEE Signal Processing Society,
出版年份2013
月份12
日期11
頁次122 - 126
國際標準書號9781479910434
語言英式英語
關鍵詞factorial HMM, speech separation, structured mean field approximation, variational method

上次更新時間 2021-18-01 於 00:44