Blind source separation is an advanced statistical tool that has found widespread use in many signal processing applications. However, the crux topic based on one channel audio source separation has not fully developed to enable its way to laboratory implementation. The main idea approach to single channel blind source separation is based on exploiting the inherent time structure of sources known as basis filters in time domain that encode the sources in a statistically efficient manner. This paper proposes a technique for separating single channel recording of audio mixture using a hybrid of maximum likelihood and maximum a posteriori estimators. In addition, the algorithm proposes a new approach that accouuts for the time structure of the speech signals by encoding them into a set of basis filters that are characteristically the most significant.
|Number of pages||10|
|Journal||WSEAS Transactions on Signal Processing|
|Publication status||Published - 1 Apr 2008|