Incorporating Gammatone Filterbank and Welch Spectral Estimation in Subband Processing-Based Localization of Multiple Simultaneous Speakers

This research addresses the problem of multiple speakers localization by applying Generalized Cross-Correlation (GCC)-band techniques on different frequency subbands. To improve the localization performance in the presence of noise and reverberation, we promote the baseline method in two folds; in the first part, human auditory-based filters are proposed for subband processing. GammaTone filterbank is the most important group of these filters. The GammaTone filterbank increases the frequency resolution in low frequencies and provides better utilization of the speech spectral information. The GammaTone filter is applied to the whole speech signal spectrum. In the second part of the proposed method, the aim is to consider the speech spectra more intelligently in the process of the localization. To this end, we use different spectral estimation methods to select the part of speech spectrum that has useful information. By comparing various spectral estimation techniques, Welch method has been selected as the best one for speech spectrum estimation. We can decrease the computational complexity and increase the accuracy using Welch estimation method. The proposed method has been examined in different acoustical environments for real and simulated data to show its superiority over the other methods. © 2017 Elsevier Ltd