MLPs and Mixture Models for the Estimation of the Posterior Probabilities of Class Membership

Authors:
Alexei V. Ivanov;Alexander A. Petrovsky
Affiliations:
-;-
Venue:
TSD '99 Proceedings of the Second International Workshop on Text, Speech and Dialogue
Year:
1999

Citing 4
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Abstract

In this paper the MLP and Gaussian mixture model approaches to the estimation of the posterior probability of class membership in the task of phoneme identification are analyzed. The paper discuss differences between the described methods altogether with discussing advantages and drawbacks of each method. Based on this analysis several ways of the joint employment of the models are proposed.