2001: A Speaker Odyssey - The Speaker Recognition Workshop

June 18-22, 2001
Crete, Greece

Bayesian Approach Based Decision in Speaker Verification

Corinne Fredouille, Jean-Francois Bonastre, Teva Merlin

LIA/CERI, Université d’Avignon, France

Considering Bayesian decision framework applied in the context of speaker verification, this paper presents a new way of handling troublesome anti-speaker model by proposing a redefinition of hypotheses involved in the classical statistical hypothesis test. This new definition is then implemented through a speaker independent normalization technique, named MAP approach. It adds the advantages of projecting likelihood scores into a probabilistic domain and therefore of providing the decision threshold with bounded and meaningful values.

In this paper, different variants of MAP approach are presented to reduce likelihood variability. MAP approach is firstly combined with classical normalization techniques. The second kind of variants consists in making MAP approach speaker dependent. Experiments conducted on a subset of Switchboard database have shown that MAP approach is able to perform as well as classical normalization techniques while yielding probabilistic scores suitable for the decision threshold setting or the fusion of multiple recognizer scores.


Full Paper   Presentation

Bibliographic reference.  Fredouille, Corinne / Bonastre, Jean-Francois / Merlin, Teva (2001): "Bayesian bpproach based decision in speaker verification", In ODYSSEY-2001, 77-81.