1 research outputs found
Statistical Modeling in Continuous Speech Recognition (CSR)(Invited Talk)
Automatic continuous speech recognition (CSR) is sufficiently mature that a
variety of real world applications are now possible including large vocabulary
transcription and interactive spoken dialogues. This paper reviews the
evolution of the statistical modelling techniques which underlie current-day
systems, specifically hidden Markov models (HMMs) and N-grams. Starting from a
description of the speech signal and its parameterisation, the various
modelling assumptions and their consequences are discussed. It then describes
various techniques by which the effects of these assumptions can be mitigated.
Despite the progress that has been made, the limitations of current modelling
techniques are still evident. The paper therefore concludes with a brief review
of some of the more fundamental modelling work now in progress.Comment: Appears in Proceedings of the Seventeenth Conference on Uncertainty
in Artificial Intelligence (UAI2001