Multi-dialect speech recognition method and apparatus

Abstract

Apparatus and method for improving the speed an accuracy of recognition of speech dialects, or speech tansferred via dissimilar channels is described. The invention provides multiple models tailored to specific segments or dialects, and/or speech channels, of the population. However, there is not a proportional increase in recognition time or computing power or computing resources needed. Probability density functions for the acoustic descriptors are provided which are shared among the various models. Since there is a common pool of probability density functions which are mapped or pointed to for the different acoustic descriptors for each different dialect or speech channel model, the memory requirements for the speech recognition apparatus and method are significantly reduced. Each model is comprised of triphonemes which are modelled by discrete probability distribution functions forming hidden Markov models or statistical word models. Any one probability density function is assigned or mapped to many different triphonemes in many different dialects or different models. The invention provides for an automatic selection of the best model in real time wherein the best fit is determined by a voting process.

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