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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Zhong Zhang Aoki, Y. Toda, H. Miyake, T. Imamura, T. |
| Copyright Year | 2009 |
| Description | Author affiliation: Department of Production System Engineering, Toyohashi University of Technology, Tempaku-cho, Toyohashi-shi, Japan (Zhong Zhang; Aoki, Y.; Toda, H.; Miyake, T.; Imamura, T.) |
| Abstract | It is well known that in real world source separation, the environment noise removal must be considered with complex reverberating sound, and various noises. In this study, in order to improve the voice recognition accuracy in real world source separation, a new method that uses Independent Component Analysis (ICA) in the time-frequency domain using the variable density complex discrete wavelet transform (VD-CDWT) and the subspace method has been proposed. Through comparison of the results according to signal noise ratio (SNR), the effectiveness of the proposed method is confirmed. |
| Starting Page | 247 |
| Ending Page | 252 |
| File Size | 1043999 |
| Page Count | 6 |
| File Format | |
| ISBN | 9781424437283 |
| DOI | 10.1109/ICWAPR.2009.5207450 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2009-07-12 |
| Publisher Place | China |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Time-frequency analysis Source separation Wavelet domain Wavelet transform Independent component analysis Time frequency analysis Wavelet analysis Discrete wavelet transforms Sound source Acoustic noise Working environment noise Speech recognition Signal to noise ratio |
| Content Type | Text |
| Resource Type | Article |
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