Presentation | 2007-12-11 Impact Noise Suppression for Speech Signals by Using a Morphological Component Analysis with DFT Hiroaki HAYASHI, Makoto NAKASHIZUKA, Youji IIGUNI, |
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Abstract(in English) | Morphological component analysis (MCA) is a signal separation method using sparse signal representations. For separation by the MCA, the set of bases are defined. Each source is assumed to be represented by one of the bases sparsely. In this paper, we propose an impact noise suppression by using the MCA. In our approach, the DFT bases and the set of shifted impluses are employed for representation of speeches and noises, respectively. To perform the separation, the sparsity measure is imposed on the distributions of DFT spectrum. In experiments, we demonstrate that noise reduction capability of the proposed method for various impact noises. |
Keyword(in Japanese) | (See Japanese page) |
Keyword(in English) | Noise Supression / Sparse Signal Separation / Impact Noises / DFT Bases / Speech Processing |
Paper # | SIS2007-66 |
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Committee | SIS |
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Conference Date | 2007/12/4(1days) |
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Registration To | Smart Info-Media Systems (SIS) |
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Language | JPN |
Title (in Japanese) | (See Japanese page) |
Sub Title (in Japanese) | (See Japanese page) |
Title (in English) | Impact Noise Suppression for Speech Signals by Using a Morphological Component Analysis with DFT |
Sub Title (in English) | |
Keyword(1) | Noise Supression |
Keyword(2) | Sparse Signal Separation |
Keyword(3) | Impact Noises |
Keyword(4) | DFT Bases |
Keyword(5) | Speech Processing |
1st Author's Name | Hiroaki HAYASHI |
1st Author's Affiliation | Graduate School of Engineering Science, Osaka University() |
2nd Author's Name | Makoto NAKASHIZUKA |
2nd Author's Affiliation | Graduate School of Engineering Science, Osaka University |
3rd Author's Name | Youji IIGUNI |
3rd Author's Affiliation | Graduate School of Engineering Science, Osaka University |
Date | 2007-12-11 |
Paper # | SIS2007-66 |
Volume (vol) | vol.107 |
Number (no) | 374 |
Page | pp.pp.- |
#Pages | 6 |
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