Importance

Loading Importance Indicators...

Abstract

A method determines if a portion of speech corresponds to a speech pattern by time aligning both the speech and a plurality of speech pattern models against a common time-aligning model. This compensates for speech variation between the speech and the pattern models. The method then compares the resulting time-aligned speech model against the resulting time-aligned pattern models to determine which of the patterns most probably corresponds to the speech. Preferably there are a plurality of time-aligning models, each representing a group of somewhat similar sound sequences which occur in different words. Each of these time-aligning models is scored for similarity against a portion of speech, and the time-aligned speech model and time-aligned pattern models produced by time alignment with the best scoring time-aligning model are compared to determine the likelihood that each speech pattern corresponds to the portion of speech. This is performed for each successive portion of speech. When a portion of speech appears to correspond to a given speech pattern model, a range of likely start times is calculated for the vocabulary word associated with that model, and a word score is calculated to indicate the likelihood of that word starting in that range. The method uses a more computationally intensive comparison between the speech and selected vocabulary words, so as to more accurately determine which words correspond with which portions of the speech. When this more intensive comparison indicates the ending of a word at a given point in the speech, the method selects the best scoring vocabulary words whose range of start times overlaps that ending time, and performs the computationally intensive comparison on those selected words starting at that point in the speech.

Loading the Abstract Image...

First Claim