Hidden markov model for speech processing with training method

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United States of America Patent

PATENT NO 9020816
APP PUB NO 20110208521A1
SERIAL NO

13059048

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Abstract

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A method, system and apparatus are shown for identifying non-language speech sounds in a speech or audio signal. An audio signal is segmented and feature vectors are extracted from the segments of the audio signal. The segment is classified using a hidden Markov model (HMM) that has been trained on sequences of these feature vectors. Post-processing components can be utilized to enhance classification. An embodiment is described in which the hidden Markov model is used to classify a segment as a language speech sound or one of a variety of non-language speech sounds. Another embodiment is described in which the hidden Markov model is trained using discriminative learning.

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Patent Owner(s)

  • 21CT, INC.

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Inventor(s)

Inventor Name Address # of filed Patents Total Citations
McClain, Matthew Austin, US 1 29

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