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Growing Phonetic Baseforms From Multiple Utterances in Speech Recognition

IP.com Disclosure Number: IPCOM000039977D
Original Publication Date: 1987-Sep-01
Included in the Prior Art Database: 2005-Feb-01

Publishing Venue

IBM

Related People

Authors:
Bahl, LR Brown, PF de Souza, PV Mercer, RL [+details]

Abstract

The most likely sequence of hidden Markov model phones which constitute a vocabulary word is determined by (a) generating a string Si(where 1 & i & n) of labels (speech prototype vectors) for each of n utterances of a word; (b) determining the probability of each string Si given a prescribed sequence Pj of phones; (c) computing (d) multiplying Pragg by the prior probability of Pj to provide a joint probability; (e) repeating steps (a) through (d) for each of a plurality of phone sequences Pj; and (f) by iterative stack decoding, determining which phone sequence has the best joint probability (for the Si strings) above a prescribed threshold. The stack decoding involves determining a first probability measure based on acoustics and a second probability measure based on a language model.