Features extracted using frequency-time analysis approach from nyquist filter bank and Gaussian filter bank for text-independent speaker identification

Abstract

This paper compares the feature sets extracted using frequency-time analysis approach and time-frequency analysis approach for text-independent speaker identification. The impetus for the frequency-time analysis approach comes from the band pass filtering view of STFT. Nyquist filter bank and Gaussian filter bank both have been used for extracting features using frequency-time analysis approach. Experimental evaluation was conducted on the POLYCOST database with 130 speakers using Gaussian mixture speaker model. Results reveal that, the feature sets extracted using frequency-time analysis approach performs significantly better compared to the feature set extracted using time-frequency analysis approach. © 2011 Springer-Verlag.