基于多任务稀疏表达的二元麦克风小阵列话音增强算法

doi:10.3969/j.issn.1000-436x.2014.02.012

Abstract

Abstract:

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/ ₁e 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.

Key words: small microphone arrays, speech enhancement, dictionary learning, multi-task sparse representation

Li-chun YANG,Min-chao YE,Yun-tao QIAN. Speech enhancement based on multi-task sparse representation for dual small microphone arrays[J]. Journal on Communications, 2014, 35(2): 87-94.

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References 25

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噪声		不同方法的得分
噪声	GSC	相干滤波器	本文方法
babble	2.7	3.4	3.7
汽车	3.1	3.5	4.0
工厂	2.6	3.3	3.9
音乐	2.6	3.1	4.0
办公室	2.8	3.4	3.8

噪声		不同信号的信噪比/dB
噪声	输入信号	GSC相干滤波器	本文方法
babble	0.87	8.0111.23	11.80
汽车	7.92	18.3820.06	21.0
工厂	-8.23	-1.984.96	5.51
音乐	-3.62	3.695.15	5.46
办公室	3.19	12.3114.68	15.19

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Speech enhancement based on multi-task sparse representation for dual small microphone arrays

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