Zhaogui Ding

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A novel multi-channel speech enhancement technique is proposed in the present paper. We focus on the local sparsities of speech signals in contrast to the conventional beamforming and blind source seperation methods. The technique utilizes the difference of local structures in temporary-frequency domain between the target speech and interfering signals for(More)
Speech enhancement is an important task in many applications such as speech recognition. Conventional methods always require some principles by which to distinguish speech and noise and the most successful enhancement requires strong models for both speech and noise. However, if the noise actually encountered differs significantly from the system's(More)
In this letter, we present a novel speech separation scheme using two microphones. We divide the inter-phase information into sub-segments and statistic these directional segments. Then we construct the objective function by convolving the statistics information with a low pass filter. By the decreasing gradient algorithm and ideal binary mask, we obtain(More)
In speech separation tasks, many separation methods have the limitation that the microphones are closely spaced, which means that these methods are unprevailing for phase wrap-around. In this paper, we present a novel speech separation scheme by using two microphones that does not have this restriction. The technique utilizes the estimation of interaural(More)
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