Speech enhancement based on multi-task sparse representation for dual small microphone arrays
Speech enhancement algorithms for dual small microphone arrays usually rely on the voice activity detec-tion(VAD), and they may fail in some cases when target speech signal is included in the first frame. A multi-task sparse representation based speech enhancement algorithm was proposed. First, dict...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | zho |
| Published: |
Editorial Department of Journal on Communications
2014-02-01
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| Series: | Tongxin xuebao |
| Subjects: | |
| Online Access: | http://www.joconline.com.cn/zh/article/doi/10.3969/j.issn.1000-436x.2014.02.012/ |
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| Summary: | Speech enhancement algorithms for dual small microphone arrays usually rely on the voice activity detec-tion(VAD), and they may fail in some cases when target speech signal is included in the first frame. A multi-task sparse representation based speech enhancement algorithm was proposed. First, dictionaries for signal and noise were respec-tively formed via dictionary learning. Then the noise in signals obtain from two microphones was reduced by e2/ <sub>1</sub>e regu-larized sparse representation on the over-complete dictionary, while the target speech signals were mostly preserved, hence the speech signals were enhanced. Experimental results from synthetic and real-world data show that the proposed speech enhancement algorithm without VAD works well in all cases no matter speech signal is included in the first frame or not. |
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| ISSN: | 1000-436X |