EUROSPEECH 2001 Scandinavia
7th European Conference on Speech Communication and Technology

Aalborg, Denmark
September 3-7, 2001


Bayesian Methods for HMM Speech Recognition with Limited Training Data

Darryl W. Purnell, Elizabeth C. Botha

University of Pretoria, South Africa

This paper presents a Bayesian approach to learning for HMMs in speech recognition. The implementation of Bayesian learning for HMMs in speech recognition is discussed, including the requirement of maintaining the original HMM constraints, choice of prior and utterance recognition. This work shows that the Bayesian learning approach can be successfully applied to complex models when the amount of training data is small.

Full Paper

Bibliographic reference.  Purnell, Darryl W. / Botha, Elizabeth C. (2001): "Bayesian methods for HMM speech recognition with limited training data", In EUROSPEECH-2001, 1249-1252.