EUROSPEECH '97
5th European Conference on Speech Communication and Technology

Rhodes, Greece
September 22-25, 1997


A Double Gaussian Mixture Modeling Approach to Speaker Recognition

Rivarol Vergin, Douglas O'Shaughnessy

CML Technologies, Quebec, Canada INRS-Telecommunications, Quebec, Canada

The first motivation for using Gaussian mixture models for text-independent speaker identification is based on the observation that a linear combination of gaussian basis functions is capable of representing a large class of sample distributions. While this technique gives generally good results, little is known about which specific part of a speech signal best identifies a speaker. This contribution suggests a procedure, based on the Jensen divergence measure, to automatically extract from the input speech signal the part that best contribute to identify a speaker. It is shown, by results obtained, that this technique can significantly increase the performance of a speaker recognition system.

Full Paper

Bibliographic reference.  Vergin, Rivarol / O'Shaughnessy, Douglas (1997): "A double Gaussian mixture modeling approach to speaker recognition", In EUROSPEECH-1997, 2287-2290.