Speech enhancement based on multi-task sparse representation for dual small microphone arrays - Li-chun YANG; Min-chao YE; Yun-tao QIAN (Tongxin xuebao)
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.