Feneme-based Markov models for words

Details Feneme-based Markov models for words Feneme-based Markov models for words

1989-06-12

1992-11-17

Fleming, Michael R.

Electrical audio signal processing systems and devices

Hearing aids, electrical

Specified casing or housing

381 43, G10L 506

Patent

active

051650070

ABSTRACT:
In a speech recognition system, apparatus and method for modelling words with label-based Markov models is disclosed. The modelling includes: entering a first speech input, corresponding to words in a vocabulary, into an acoustic processor which converts each spoken word into a sequence of standard labels, where each standard label corresponds to a sound type assignable to an interval of time; representing each standard label as a probabilistic model which has a plurality of states, at least one transition from a state to a state, and at least one settable output probability at some transitions; entering selected acoustic inputs into an acoustic processor which converts the selected acoustic inputs into personalized labels, each personalized label corresponding to a sound type assigned to an interval of time; and setting each output probability as the probability of the standard label represented by a given model producing a particular personalized label at a given transition in the given model. The present invention addresses the problem of generating models of words simply and automatically in a speech recognition system.

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Reprinted from IEEE Trans. Acoust., Speech, and Signal Process., vol. ASSP-23, pp. 67-72, Feb. 1975, "Minimum Prediction Residual Principle Applied to Speech Recognition", by Fumitada Itakura.

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