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

Authors:
Nirmalya Sen;T. K. Basu
Affiliations:
Signal Processing Research Group, C.E.T, IIT Kharagpur, India;Electrical Engineering Department, IIT Kharagpur, India
Venue:
BioID'11 Proceedings of the COST 2101 European conference on Biometrics and ID management
Year:
2011

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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.