Group Delay Based Methods for Speaker Segregation and its Application in Multimedia Information Retrieval

Abstract

A novel method of single channel speaker segregation using the group delay cross correlation function is proposed in this paper. The group delay function, which is the negative derivative of the phase spectrum, yields robust spectral estimates. Hence the group delay spectral estimates are first computed over frequency sub-bands after passing the speech signal through a bank of filters. The filter bank spacing is based on a multi-pitch algorithm that computes the pitch estimates of the competing speakers. An affinity matrix is then computed from the group delay spectral estimates of each frequency sub-band. This affinity matrix represents the correlations of the different sub-bands in the mixed broadband speech signal. The grouping of correlated harmonics present in the mixed speech signal is then carried out by using a new iterative graph cut method. The signals are reconstructed from the respective harmonic groups which represent individual speakers in the mixed speech signal. Spectrographic masks are then applied on the reconstructed signals to refine their perceptual quality. The quality of separated speech is evaluated using several objective and subjective criteria. Experiments on multi-speaker automatic speech recognition are conducted using mixed speech data from the GRID corpus. A cell phone based multimedia information retrieval system (MIRS) for multi-source meeting environments are also developed.