Design of speech recognition engine

Abstract

This paper concerns a speaker independent recognition engine of Czech continuous speech designed for Czech telephone applications and describes the recognition module as an important component of a telephone dialogue system being designed and constructed at the Department of Cybernetics, the University of West Bohemia. The recognition is based on a statistical approach. The leftto-right three-state HMMs with an output probability density function expressed as multivariate Gaussian mixture are used to model triphones as basic units in acoustic modelling and stochastic regular grammars are implemented to reduce a task perplexity. Areal time recognition process is supported by a very computation cost reduction approach estimating log-likelihood scores of Gaussian mixtures and also by a beam pruning used during Viterbi decoding. The present paper concerns the main part of the engine–a speaker independent recognition engine for continuous Czech speech.