Automatic recognition of spoken words from a large vocabulary using syllable templates

A system is proposed for automatic speech recognition using syllable templates. In this system, input speech signal is analyzed and matched against syllable templates and converted into parameters characterizing each candidate syllable. Word recognition is based on an overall likelihood measure calculated for each item stored in the lexicon. A method is also developed for the optimization of syllable templates. The validity of the proposed method was tested in a preliminary recognition experiment in which a lexicon consisting of 1000 city names was used to recognize utterances of 100 city names by a female speaker. The rate of correct recognition was 96.5%.