Speech recognition system using Markov models having independent label output sets

摘要

A speech recognition system measures the values of at least two classes of features of an utterance: (1) a first class whose value is related to the frequency spectrum of the utterance, and (2) a second class whose value is related to the variation with time of the "first class" value of the utterance. Word baseforms are constructed from Markov model baseform units. Each output-producing transition of a baseform unit produces outputs from both classes. However, for each output-producing transition, the probabilities of producing outputs from the first class are independent of the probabilities of producing outputs from the second class.