Importance

Loading Importance Indicators...

Abstract

A first speech recognition method receives an acoustic description of an utterance to be recognized and scores a portion of that description against each of a plurality of cluster models representing similar sounds from different words. The resulting score for each cluster is used to calculate a word score for each word represented by that cluster. Preferably these word scores are used to prefilter vocabulary words, and the description of the utterance includes a succession of acoustic decriptions which are compared by linear time alignment against a succession of acoustic models. A second speech recognition method is also provided which matches an acoustic model with each of a succession of acoustic descriptions of an utterance to be recognized. Each of these models has a probability score for each vocabulary word. The probability scores for each word associated with the matching acoustic models are combined to form a total score for that word. The preferred speech recognition method calculates to separate word scores for each currently active vocabulary word from a common succession of sounds. Preferably the first scores is calculated by a time alignment method, while the second score is calculated by a time independent method. Preferably this calculation of two separate word scores is used in one of multiple word-selecting phase of a recognition process, such as in the prefiltering phase.

Loading the Abstract Image...

First Claim