文章基本信息

标题：A Hybrid Approach for Co-Channel Speech Segregation based on CASA, HMM Multipitch Tracking, and Medium Frame Harmonic Model
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作者：Ashraf M. Mohy Eldin ; Aliaa A. A. Youssif
期刊名称：International Journal of Advanced Computer Science and Applications(IJACSA)
印刷版ISSN：2158-107X
电子版ISSN：2156-5570
出版年度：2013
卷号：4
期号：7
DOI：10.14569/IJACSA.2013.040721
出版社：Science and Information Society (SAI)
摘要：This paper proposes a hybrid approach for co-channel speech segregation. HMM (hidden Markov model) is used to track the pitches of 2 talkers. The resulting pitch tracks are then enriched with the prominent pitch. The enriched tracks are correctly grouped using pitch continuity. Medium frame harmonics are used to extract the second pitch for frames with only one pitch deduced using the previous steps. Finally, the pitch tracks are input to CASA (computational auditory scene analysis) to segregate the mixed speech. The center frequency range of the gamma tone filter banks is maximized to reduce the overlap between the channels filtered for better segregation. Experiments were conducted using this hybrid approach on the speech separation challenge database and compared to the single (non-hybrid) approaches, i.e. signal processing and CASA. Results show that using the hybrid approach outperforms the single approaches.
关键词：thesai; IJACSA; thesai.org; journal; IJACSA papers; CASA (computational auditory scene analysis); co-channel speech segregation; HMM (hidden Markov model) tracking; hybrid speech segregation approach; medium frame nic model; multipitch tracking; prominent pitch.