Third International Conference on Spoken Language Processing (ICSLP 94)

Yokohama, Japan
September 18-22, 1994

Using Gamma Filters to Model Temporal Dependencies in Speech

Steve J. Renals, Mike M. Hochberg

Cambridge University Engineering Department, Cambridge, UK

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%.

Full Paper

Bibliographic reference.  Renals, Steve J. / Hochberg, Mike M. (1994): "Using gamma filters to model temporal dependencies in speech", In ICSLP-1994, 1491-1494.