Performance comparison of HMM and VQ based single channel speech separation

In this paper, single channel speech separation (SCSS) techniques based on hidden Markov models (HMM) and vector quantization (VQ) are described and compared in terms of (a) signal-to-noise ratio (SNR) between separated and original speech signals, (b) preference of listeners, and (c) computational complexity. The SNR results show that the HMMbased technique marginally outperforms the VQ-based technique by 0.85 dB in experiments conducted on mixtures of female-female, male-male, and male-female speakers. Subjective tests show that listeners prefer HMM over VQ for 86.70 % of test speech files. This improvement, however, is at the expense of a drastic increase in computational complexity when compared with the VQ-based technique.