ISCA Archive ICSLP 1994
ISCA Archive ICSLP 1994

Using gamma filters to model temporal dependencies in speech

Steve J. Renals, Mike M. Hochberg

Hybrid systems which use connectionist networks to estimate the output probabilities of a hidden Markov model represent time both at the network level and the Markov chain level. In this paper we discuss modelling time in connectionist networks, and introduce local recurrences in a feed-forward network in the form of an adaptive gamma filter. Using the Resource Management (RM) database, we have performed continuous speech recognition experiments comparing a gamma filtered input representation to a delay line. We have also performed speaker adaptation experiments using the speaker-dependent RM database. Our results have not indicated that gamma filters offer an appreciable modelling advantage on this task. However, the baseline speaker adaptation experiments have indicated that supervised adaptation over 100 sentences reduced the word error by an average of 40%.


Cite as: Renals, S.J., Hochberg, M.M. (1994) Using gamma filters to model temporal dependencies in speech. Proc. 3rd International Conference on Spoken Language Processing (ICSLP 1994), 1491-1494

@inproceedings{renals94_icslp,
  author={Steve J. Renals and Mike M. Hochberg},
  title={{Using gamma filters to model temporal dependencies in speech}},
  year=1994,
  booktitle={Proc. 3rd International Conference on Spoken Language Processing (ICSLP 1994)},
  pages={1491--1494}
}