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Blind separation of speech signals based on wavelet transform and independent component analysis |
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| Authors: | WU Xiao HE Jingjing JIN Shijiu XU Antao WANG Weikui |
| Institution: | 1. School of Precision Instrument and Opto-Electronics Engineering, Tianjin University, Tianjin 300072, China;Department of Automotive Engineering, Military Transportation Institute of Tianjin, Tianjin 300161, China 2. School of Precision Instrument and Opto-Electronics Engineering, Tianjin University, Tianjin 300072, China 3. Department of Automotive Engineering, Military Transportation Institute of Tianjin, Tianjin 300161, China |
| Abstract: | Speech signals in frequency domain were separated based on discrete wavelet transform (DWT) and independent component analysis (ICA). First, mixed speech signals were decomposed into different frequency domains by DWT and the subbands of speech signals were separated using ICA in each wavelet domain; then, the permutation and scaling problems of frequency domain blind source separation (BSS) were solved by utilizing the correlation between adjacent bins in speech signals; at last, source signals were recons... |
| Keywords: | wavelet transform independent component analysis blind source separation |
| 本文献已被 CNKI 维普 万方数据 SpringerLink 等数据库收录！ | |