Dynamic classifier combination in hybrid speech recognition systems using utterance-level confidence values

Authors:
K. Kirchhoff;J. A. Bilmes
Affiliations:
AG Angewandte Inf., Bielefeld Univ., Germany;-
Venue:
ICASSP '99 Proceedings of the Acoustics, Speech, and Signal Processing, 1999. on 1999 IEEE International Conference - Volume 02
Year:
1999

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Abstract

A recent development in the hybrid HMM/ANN speech recognition paradigm is the use of several subword classifiers, each of which provides different information about the speech signal. Although the combining methods have obtained promising results, the strategies so far proposed have been relatively simple. In most cases frame-level subword unit probabilities are combined using an unweighted product or sum rule. In this paper, we argue and empirically demonstrate that the classifier combination approach can benefit from a dynamically weighted combination rule, where the weights are derived from higher-than-frame-level confidence values.