Patent ID: 6336108
Filing Date: 2002-01-01
Classification: G06K,G06N,Y10S

Abstract:
A speech recognition network for inferring parts of speech from acoustic observations having n elements, with a common hidden variable having plural discrete states, comprising:a plurality of mixtures of Bayesian networks (MBNs), each of said MBNs encoding the probabilities of observing the sets of acoustic observations given the utterance of a respective one of said parts of speech; each of said MBNs comprising: a plurality of hypothesis-specific Bayesian networks (HSBNs), each of said HSBNs encoding the probabilities of observing the sets of acoustic observations given the utterance of a respective one of said parts of speech and given the hidden common variable being in a respective one of its states; a combiner which combines outputs of said HSBNs to produce an MBN output of said MBN; wherein each one of said HSBNs comprises: plural nodes, each of said nodes corresponding to one of said n elements of the acoustic observations, at least some of said plural nodes having dependencies with others of said plural nodes within the one HSBN, a combiner connected to outputs of said nodes, said nodes receiving at their inputs the state of a respective one of the n elements of a current one of the acoustic observations.