Speech separation with EMD as front-end for noise robust co-channel speaker identification

This work deals with front end processing of co-channel speaker identification problem. A co-channel speech consists of mixture of speech signals from two speakers and one microphone. Most of the methods on speaker identification work well for noise free and single speaker environment and the performance reduces under noisy and multi speaker environment. We propose EMD (Empirical mode decomposition) based denoising at the front end along with pitch estimation to separate the co-channel speech mixture. Results show that speaker id correct rate increases after denoising and separating the speakers from the mixture using proposed method at the front end of speaker identification.