Method for uncovering hidden Markov models

Details Method for uncovering hidden Markov models Method for uncovering hidden Markov models

2011-03-22

2011-03-22

Wozniak, James S (Department: 2626)

Data processing: speech signal processing, linguistics, language

Speech signal processing

Recognition

C704S256100, C704S256200, C704S256500, C704S256600, C704S251000, C704S254000, C704S255000, C704S240000, C706S020000, C706S021000

Reexamination Certificate

active

07912717

ABSTRACT:
The invention uses the ModelGrower program to generate possible candidates from an original or aggregated model. An isomorphic reduction program operates on the candidates to identify and exclude isomorphic models. A Markov model evaluation and optimization program operates on the remaining non-isomorphic candidates. The candidates are optimized and the ones that most closely conform to the data are kept. The best optimized candidate of one stage becomes the starting candidate for the next stage where ModelGrower and the other programs operate on the optimized candidate to generate a new optimized candidate. The invention repeats the steps of growing, excluding isomorphs, evaluating and optimizing until such repetitions yield no significantly better results.

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