Pattern and speech recognition using accumulated partial scores from a posteriori odds, with pruning based on calculation amount
First Claim
1. A pattern recognition method for classifying a continuous pattern representative of a physical activity or phenomenon to one or predetermined classes each indicating a combination of one or more predetermined subclasses, comprising:
- a first step of determining a plurality of partial scores each indicating an estimate of logarithm of a posteriori odds that one of partial patterns of said continuous pattern is classified to one of said subclasses;
a second step of determining accumulated scores each indicating summation of one or more of said partial scores; and
a third step of classifying said continuous pattern into one of said predetermined classes based on said determined accumulated scores, whereinscores of any possible partial patterns are used, andthe partial patterns are not first isolated.
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Abstract
A speech recognition apparatus includes a data input portion to which input data which is a speech pattern is applied, a score calculation portion calculating a score indicating a possibility of recognition of a partial pattern of the speech pattern based on the estimate of a posteriori odds, an optimization design portion designing optimized parameters for calculating the estimate of the a posteriori odds in the score calculation portion and/or optimized parameters of pruning functions controlling calculation amount in the pruning processing portion, a pruning processing portion pruning the score for making operation efficient, an accumulated score calculating portion accumulating pruned scores to calculate an accumulated score, a recognition result decision portion classifying input data for every class based on the accumulated score and deciding a recognition result, and a recognition result output portion providing the recognition result.
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Citations
30 Claims
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1. A pattern recognition method for classifying a continuous pattern representative of a physical activity or phenomenon to one or predetermined classes each indicating a combination of one or more predetermined subclasses, comprising:
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a first step of determining a plurality of partial scores each indicating an estimate of logarithm of a posteriori odds that one of partial patterns of said continuous pattern is classified to one of said subclasses; a second step of determining accumulated scores each indicating summation of one or more of said partial scores; and a third step of classifying said continuous pattern into one of said predetermined classes based on said determined accumulated scores, wherein scores of any possible partial patterns are used, and the partial patterns are not first isolated. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10)
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11. A speech recognition method for classifying a time series speech pattern representative of a physical activity or phenomenon to one of predetermined classes each indicating a combination of one or more predetermined subclasses, comprising:
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a first step of determining a plurality of partial scores each indicating an estimate of logarithm of a posteriori odds that one of partial patterns of said speech pattern is classified to one of said subclasses; a second step of determining accumulated scores each indicating summation of one or more of said partial scores; and a third step of classifying said speech pattern into one of said predetermined classes based on said determined accumulated scores, wherein scores of any possible partial patterns are used, and the partial patterns are not first isolated. - View Dependent Claims (12, 13, 14, 15, 16, 17, 18, 19, 20)
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21. A speech recognition apparatus for classifying a time series speech pattern representative of a physical activity or phenomenon to one of predetermined classes each indicating a combination of one or more predetermined subclasses, comprising:
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score determination means for determining a plurality of partial scores each indicating an estimate of logarithm of a posteriori odds that one of partial patterns of said speech pattern is classified to one of said subclasses; accumulated score determination means for determining accumulated scores each indicating summation of one or more of said partial scores; and classification means for classifying said speech pattern into one of said predetermined classes based on said determined accumulated scores, wherein scores of any possible partial patterns are used, and the partial patterns are not first isolated. - View Dependent Claims (22, 23, 24, 25, 26, 27, 28, 29, 30)
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Specification