Pattern adapting apparatus using minimum description length criterion in pattern recognition processing and speech recognition system
First Claim
1. A pattern adapting apparatus for adapting standard patterns made up of a plurality of categories to individual targets by learning that employs an input pattern as a set of input samples, comprising:
- input pattern forming means for forming an input pattern;
tree structure standard pattern storing means for storing a tree structure standard pattern including a tree structure indicative of inclusive relationships among categories and a set of parameters at each node of the tree structure;
pattern matching means for matching the categories of said tree structure standard pattern with the input samples of said input pattern;
tree structure standard pattern modifying means for modifying said tree structure standard pattern based on the results of pattern matching by said pattern matching means;
node set selecting means for calculating a description length with respect to a plurality of node sets in said tree structure pattern to select an appropriate node set according to the calculated description length;
modified standard pattern forming means for forming a modified standard pattern by using a parameter set of the node set selected by said node set selecting means; and
standard pattern for recognition storing means for storing a modified standard pattern formed by said modified standard pattern forming means,wherein said pattern matching means performs pattern matching by using, as a parameter, at least one of;
i) a mean vector of an output probability distribution of said standard pattern, ii) a variance of the output probability distribution of said standard pattern, and iii) a weighting factor at a state of said standard pattern.
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Abstract
A pattern adapting apparatus including an input pattern forming unit, a tree structure standard pattern storing unit for storing a tree structure standard pattern including a tree structure indicative of inclusive relationships among categories and a parameter set at each node of the tree structure, a pattern matching unit for matching categories of the tree structure standard pattern with input samples of an input pattern, a tree structure standard pattern modifying unit for modifying a tree structure standard pattern based on the results of pattern matching, a node set selecting unit for calculating a description length with respect to a plurality of node sets in a tree structure pattern to select an appropriate node set, a modified standard pattern forming unit for forming a modified standard pattern by using a parameter set of a selected node set, and a standard pattern for recognition storing unit for storing a modified standard pattern.
38 Citations
19 Claims
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1. A pattern adapting apparatus for adapting standard patterns made up of a plurality of categories to individual targets by learning that employs an input pattern as a set of input samples, comprising:
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input pattern forming means for forming an input pattern; tree structure standard pattern storing means for storing a tree structure standard pattern including a tree structure indicative of inclusive relationships among categories and a set of parameters at each node of the tree structure; pattern matching means for matching the categories of said tree structure standard pattern with the input samples of said input pattern; tree structure standard pattern modifying means for modifying said tree structure standard pattern based on the results of pattern matching by said pattern matching means; node set selecting means for calculating a description length with respect to a plurality of node sets in said tree structure pattern to select an appropriate node set according to the calculated description length; modified standard pattern forming means for forming a modified standard pattern by using a parameter set of the node set selected by said node set selecting means; and standard pattern for recognition storing means for storing a modified standard pattern formed by said modified standard pattern forming means, wherein said pattern matching means performs pattern matching by using, as a parameter, at least one of;
i) a mean vector of an output probability distribution of said standard pattern, ii) a variance of the output probability distribution of said standard pattern, and iii) a weighting factor at a state of said standard pattern. - View Dependent Claims (2, 3, 12, 13)
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4. A pattern adapting apparatus for performing pattern recognition processing of an input voice as an input sample to specify a speaker of the input voice, comprising:
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tree structure standard pattern storing means for storing a tree structure standard pattern including a tree structure indicative of inclusive relationships among categories and a set of parameters at each node of the tree structure; pattern matching means for receiving an input pattern as a time series of frame vectors obtained by analyzing said input voice to match the categories of said tree structure standard pattern with an input sample of said input pattern; standard pattern modifying means for modifying said tree structure standard pattern based on the results of pattern matching by said pattern matching means; node set selecting means for calculating a description length with respect to a plurality of node sets in said tree structure pattern to select an appropriate node set according to the calculated description length; modified standard pattern forming means for forming a modified standard pattern by using a parameter set of the node set selected by said node set selecting means; and standard pattern for recognition storing means for storing a modified standard pattern formed by said modified standard pattern forming means, wherein said pattern matching means performs pattern matching by using, as a parameter, at least one of;
i) a mean vector of an output probability distribution of said standard pattern, ii) a variance of the output probability distribution of said standard pattern, and iii) a weighting factor at a state of said standard pattern. - View Dependent Claims (5, 14, 15)
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6. A pattern adapting apparatus for performing pattern recognition processing of an input voice as an input sample to specify a speaker of the input voice, comprising:
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tree structure standard pattern storing means for storing a tree structure standard pattern including a tree structure indicative of inclusive relationships among categories and a set of parameters at each node of the tree structure; pattern matching means for receiving an input pattern as a time series of frame vectors obtained by analyzing said input voice to match the categories of said tree structure standard pattern with an input sample of said input pattern; standard pattern modifying means for modifying said tree structure standard pattern based on the results of pattern matching by said pattern matching means; node set selecting means for calculating a description length with respect to a plurality of node sets in said tree structure pattern to select an appropriate node set according to the calculated description length; modified standard pattern forming means for forming a modified standard pattern by using a parameter set of the node set selected by said node set selecting means; and standard pattern for recognition storing means for storing a modified standard pattern formed by said modified standard pattern forming means, wherein a tree structure formed by using a Gaussian distribution at each state of a Hidden Markov Model whose output probability distribution is a mixed Gaussian distribution is used as said tree structure standard pattern, and wherein said pattern matching means performs pattern matching by using a mean vector of said output probability distribution as a parameter.
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7. A voice recognition system for specifying a speaker of an input voice as an input sample by performing pattern recognition processing of the input voice, including input pattern forming means for forming an input pattern as a time series of frame vectors obtained by analyzing an input voice, standard pattern storing means for storing a model of voice information source, recognition means for recognizing an input pattern based on said input pattern and said standard pattern storing means to specify a speaker of said input voice, and a pattern adapting apparatus for modifying, for an individual speaker, said model of voice information source stored in said standard pattern storing means, said pattern adapting apparatus comprising:
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tree structure standard pattern storing means for storing a tree structure standard pattern including a tree structure indicative of inclusive relationships among categories and a set of parameters at each node of the tree structure; pattern matching means for receiving an input pattern as a time series of frame vectors obtained by analyzing said input voice to match the categories of said tree structure standard pattern with an input sample of said input pattern; standard pattern modifying means for modifying said tree structure standard pattern based on the results of pattern matching by said pattern matching means; node set selecting means for calculating a description length with respect to a plurality of node sets in said tree structure pattern to select an appropriate node set according to the calculated description length; and modified standard pattern forming means for forming a modified standard pattern by using a parameter set of the node set selected by said node set selecting means to store the modified standard pattern in said standard pattern storing means in place of a model of voice information source prior to the modification, wherein said pattern matching means performs pattern matching by using, as a parameter, at least one of;
i) a mean vector of an output probability distribution of said standard pattern, ii) a variance of the output probability distribution of said standard pattern, and iii) a weighting factor at a state of said standard pattern. - View Dependent Claims (8, 16, 17)
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9. A voice recognition system for specifying a speaker of an input voice as an input sample by performing pattern recognition processing of the input voice, including input pattern forming means for forming an input pattern as a time series of frame vectors obtained by analyzing an input voice, standard pattern storing means for storing a model of voice information source, recognition means for recognizing an input pattern based on said input pattern and said standard pattern storing means to specify a speaker of said input voice, and a pattern adapting apparatus for modifying, for an individual speaker, said model of voice information source stored in said standard pattern storing means, said pattern adapting apparatus comprising:
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tree structure standard pattern storing means for storing a tree structure standard pattern including a tree structure indicative of inclusive relationships among categories and a set of parameters at each node of the tree structure; pattern matching means for receiving an input pattern as a time series of frame vectors obtained by analyzing said input voice to match the categories of said tree structure standard pattern with an input sample of said input pattern; standard pattern modifying means for modifying said tree structure standard pattern based on the results of pattern matching by said pattern matching means; node set selecting means for calculating a description length with respect to a plurality of node sets in said tree structure pattern to select an appropriate node set according to the calculated description length; and modified standard pattern forming means for forming a modified standard pattern by using a parameter set of the node set selected by said node set selecting means to store the modified standard pattern in said standard pattern storing means in place of a model of voice information source prior to the modification, wherein said pattern adapting apparatus uses, as said tree structure standard pattern, a tree structure formed by using a Gaussian distribution at each state of a Hidden Markov Model whose output probability distribution is a mixed Gaussian distribution, and wherein said pattern matching means of said pattern adapting apparatus performs pattern matching by using a mean vector of said output probability distribution as a parameter.
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10. A pattern adapting apparatus for adapting standard patterns made up of a plurality of categories to individual targets by learning that employs an input pattern as a set of input samples, comprising:
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input pattern forming means for forming an input pattern; candidate standard pattern storing means for storing a plurality of standard patterns; pattern matching means for matching the categories of said standard pattern with the input samples of said input pattern; standard pattern modifying means for modifying said standard pattern based on the results of pattern matching by said pattern matching means; description length calculating means for calculating a description length of said each modified standard pattern corresponding to said input pattern; modified standard pattern selecting means for selecting a modified standard pattern according to a description length of said standard pattern calculated by said description length calculating means; and standard pattern for recognition storing means for storing a modified standard pattern formed by said modified standard pattern selecting means, wherein said pattern matching means performs pattern matching by using, as a parameter, at least one of;
i) a mean vector of an output probability distribution of said standard pattern, ii) a variance of the output probability distribution of said standard pattern, and iii) a weighting factor at a state of said standard pattern. - View Dependent Claims (11, 18, 19)
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Specification