One microphone speech separaction with deep belief network

In this paper, we proposed a novel method for speech separation under one-microphone input. The method employs the deep belief networks to build the speech magnitude estimator, which provides a soft mask for extracting the desired speech from the input signal mixed with interference signals. The new approach has been evaluated on mixture speech data and the results demonstrated its efficiency.