Speech recognition apparatus
First Claim
1. A speech recognition apparatus using a probability model that employs a mixed distribution, said apparatus comprising:
- standard pattern storage means for storing a standard pattern of a Hidden Markov Model (HMM) having a plurality of states;
recognition means for outputting recognition results corresponding to an input speech by using said standard pattern;
standard pattern generating means for inputting learning speech and generating said standard pattern; and
standard pattern adjustment means, provided between said standard pattern generating means and said standard pattern storage means, for adjusting the number of element distributions of said mixed distribution of said standard pattern;
wherein said standard pattern adjustment means comprising;
tree structure generating means for generating a tree structure of element distributions for each state of the HMM, andelement distribution selection means for adjusting the number of element distributions of said mixed distribution of said standard pattern for each state of the HMM by selecting element distributions to leaves in said standard pattern by using said tree structure generated by said tree structure generating means after generation of said tree structure,wherein the standard pattern adjustment means calculates a description length for all possible cuts that can be made on the tree structure of element distributions, and wherein the standard pattern adjustment means selects one of the cuts having a minimum description length, in order to divide the tree structure of element distributions into a top part and a bottom part, separated by the one of the cuts.
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Accused Products
Abstract
A speech recognition apparatus using a probability model that employs a mixed distribution, the apparatus formed by a standard pattern storage means for storing a standard pattern; a recognition means for outputting recognition results corresponding to an input speech by using the standard pattern; a standard pattern generating means for inputting learning speech and generating the standard pattern; and a standard pattern adjustment means, provided between the standard pattern generating means and the standard pattern storage means, for adjusting the number of element distributions of the mixed distribution of the standard pattern.
16 Citations
14 Claims
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1. A speech recognition apparatus using a probability model that employs a mixed distribution, said apparatus comprising:
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standard pattern storage means for storing a standard pattern of a Hidden Markov Model (HMM) having a plurality of states; recognition means for outputting recognition results corresponding to an input speech by using said standard pattern; standard pattern generating means for inputting learning speech and generating said standard pattern; and standard pattern adjustment means, provided between said standard pattern generating means and said standard pattern storage means, for adjusting the number of element distributions of said mixed distribution of said standard pattern; wherein said standard pattern adjustment means comprising; tree structure generating means for generating a tree structure of element distributions for each state of the HMM, and element distribution selection means for adjusting the number of element distributions of said mixed distribution of said standard pattern for each state of the HMM by selecting element distributions to leaves in said standard pattern by using said tree structure generated by said tree structure generating means after generation of said tree structure, wherein the standard pattern adjustment means calculates a description length for all possible cuts that can be made on the tree structure of element distributions, and wherein the standard pattern adjustment means selects one of the cuts having a minimum description length, in order to divide the tree structure of element distributions into a top part and a bottom part, separated by the one of the cuts. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12)
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13. A method of controlling a speech recognition apparatus using a probability model that employs a mixed distribution, comprising the steps of:
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storing a standard pattern of a Hidden Markov Model (HMM) having a plurality of states by using a standard pattern storage means; outputting recognition results corresponding to an input speech with said standard pattern by using a recognition means; inputting learning speech and generating said standard pattern by using a standard pattern generating means; and adjusting a number of element distributions of said mixed distribution of said standard pattern by using a standard pattern adjustment means that is provided between said standard pattern generating means and said standard pattern storage means; generating a tree structure of element distributions for each state of the HMM by using a tree structure generating means; and wherein the adjusting step comprises adjusting the number of element distributions of said mixed distribution of said standard pattern for each state of the HMM by selecting element distributions to leaves in said standard pattern by using said tree structure generated by said tree structure generating means after generation of said tree structure, wherein the adjusting step further comprises; calculating a description length for all possible cuts that can be made on the tree structure of element distributions; selecting one of the cuts having a minimum description length; and dividing the tree structure of element distributions into a top part and a bottom part, separated by the one of the cuts. - View Dependent Claims (14)
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Specification