Connectionist Probability Estimators in HMM Speech Recognition (1994)
| Venue: | IEEE TRANSACTIONS ON SPEECH AND AUDIO PROCESSING |
| Citations: | 45 - 9 self |
BibTeX
@ARTICLE{Renals94connectionistprobability,
author = {Steve Renals and Nelson Morgan and Hervé Bourlard and Michael Cohen and Horacio Franco},
title = {Connectionist Probability Estimators in HMM Speech Recognition},
journal = {IEEE TRANSACTIONS ON SPEECH AND AUDIO PROCESSING},
year = {1994},
volume = {2},
number = {1},
pages = {161--174}
}
Years of Citing Articles
Bookmark
 |
 |
 |
 |
 |
 |
OpenURL
Abstract
We are concerned with integrating connectionist networks into a hidden Markov model (HMM) speech recognition system. This is achieved through a statistical interpretation of connectionist networks as probability estimators. We review the basis of HMM speech recognition and point out the possible benefits of incorporating connectionist networks. Issues necessary to the construction of a connectionist HMM recognition system are discussed, including choice of connectionist probability estimator. We describe the performance of such a system using a multilayer perceptron probability estimator evaluated on the speaker-independent DARPA Resource Management database. In conclusion, we show that a connectionist component improves a state-of-the-art HMM system.
