System and method for parameter estimation for pattern recognition
First Claim
1. A parameter estimator for estimating a set of parameters for pattern recognition, said parameter estimator comprising:
- a recognizer for receiving a training set having members and performing recognition on said members using a current set of parameters and a predetermined group of elements, a set generator associated with said recognizer for generating at least one equivalence set comprising recognized ones of said members, a target function determiner associated with said set generator for calculating from at least one of said equivalence sets a target function using said set of parameters, and a maximizer associated with said target function determiner for updating said set of parameters to maximize said target function.
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Abstract
A parameter estimator for estimating a set of parameters for pattern recognition has a recognizer for receiving a training set having members. The recognizer performs recognition on the members of the training set using a current set of parameters and based upon a predetermined group of elements. A set generator associated with the recognizer generates at least one equivalence set containing recognized members of the training set, which are used by a target function determiner associated with the set generator to calculate a target function using the set of parameters. A maximizer updates the parameter set so as to maximize the calculated target function.
61 Citations
107 Claims
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1. A parameter estimator for estimating a set of parameters for pattern recognition, said parameter estimator comprising:
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a recognizer for receiving a training set having members and performing recognition on said members using a current set of parameters and a predetermined group of elements, a set generator associated with said recognizer for generating at least one equivalence set comprising recognized ones of said members, a target function determiner associated with said set generator for calculating from at least one of said equivalence sets a target function using said set of parameters, and a maximizer associated with said target function determiner for updating said set of parameters to maximize said target function. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25)
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26. A parameter estimator for estimating a set of parameters for word-spotting pattern recognition, said parameter estimator comprising:
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a recognizer for receiving a training set, performing recognition on said training set using a current set of parameters and a predetermined group of elements, and providing recognized transcriptions of said training set, a target function determiner associated with said recognizer for calculating from at least one of said recognized transcriptions a target function using said set of parameters, and a maximizer associated with said target function determiner for updating said set of parameters to maximize said target function. - View Dependent Claims (27, 28, 29, 30, 31, 32, 33, 34, 35, 36)
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37. A pattern recognizer for performing statistical pattern recognition upon an input sequence, said pattern recognizer being operable to transcribe said input sequence into an output sequence, said output sequence comprising elements from a predetermined group of elements, said pattern recognizer comprising:
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a transcriber for performing said transcription according to a predetermined statistical model having a set of parameters, and a parameter estimator for providing said set of parameters, said parameter estimator comprising;
a recognizer for receiving a training set having members and performing recognition on said members using a current set of parameters and said predetermined group of elements, a set generator associated with said recognizer for generating at least one equivalence set comprising recognized ones of said members, a target function determiner associated with said set generator for calculating from at least one of said equivalence sets a target function using said set of parameters, and a maximizer associated with said target function determiner for updating said set of parameters to maximize said target function. - View Dependent Claims (38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52)
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53. A speech recognizer for performing statistical speech processing upon an input sequence of utterances, said speech recognizer being operable to transcribe said input sequence into an output sequence, said output sequence comprising words from a predetermined vocabulary, said speech recognizer comprising:
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a transcriber for performing said transcription according to a predetermined statistical model having a set of parameters, and a parameter estimator for providing said set of parameters, said parameter estimator comprising;
a recognizer for receiving a training set having utterances and performing recognition on said utterances using a current set of parameters and said predetermined vocabulary, a set generator associated with said recognizer for generating at least one equivalence set comprising recognized ones of said utterances, a target function determiner associated with said set generator for calculating from at least one of said equivalence sets a target function using said set of parameters, and a maximizer associated with said target function determiner for updating said set of parameters to maximize said target function. - View Dependent Claims (54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70)
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71. A parameter estimator for estimating a set of parameters for pattern recognition, said parameter estimator comprising:
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a recognizer for receiving a training set having members and performing recognition on said members using a current set of parameters and a predetermined group of elements, a set generator associated with said recognizer for generating at least one equivalence set comprising recognized ones of said members, a numerator calculator, associated with said set generator, operable to calculate, for a given parameter and a set of indices of training set members, a respective numerator accumulator, a denominator calculator associated with said set generator, operable to calculate, for said given parameter and a set of indices of training set members, a respective denominator accumulator, and an evaluator, associated with said numerator calculator and said denominator calculator, for calculating for said given parameter a quotient between the difference between a first numerator accumulator, calculated for said given parameter and a set of indices of training set members corresponding to a given element v, and a second numerator accumulator, calculated for said given parameter and a set of indices of training set members corresponding to an equivalence set associated with element v, multiplied by a discrimination rate, and, the difference between a first denominator accumulator, calculated for said given parameter and said set of indices of training set members corresponding to element v, and a second denominator accumulator, calculated for said given parameter and said set of indices of training set members corresponding to said equivalence set associated with element v, multiplied by a discrimination rate, said discrimination rate being variable between zero and one. - View Dependent Claims (72, 73, 74, 75, 76, 77)
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78. A method for estimating a set of parameters for insertion into a statistical pattern recognition process, said method comprising:
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determining initial values for said set of parameters; and
performing an estimation cycle comprising;
receiving a training set having members;
performing recognition on said members using a current set of parameters and a predetermined group of elements;
generating at least one equivalence set comprising recognized members of said training set;
using said equivalence sets and said set of parameters to calculate a target function;
maximizing said target function with respect to said set of parameters;
updating said set of parameters to maximize said target function;
if said set of parameters satisfies a predetermined estimation termination condition, outputting said parameters and discontinuing said parameter estimation method; and
if said set of parameters does not satisfy a predetermined estimation termination condition, performing another estimation cycle. - View Dependent Claims (79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92)
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93. A method for performing statistical pattern recognition upon an input sequence, thereby to transcribe said input sequence into an output sequence comprising elements from a predetermined group of elements, the method comprising the steps of:
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receiving said input sequence;
estimating a set of parameters of a statistical model by;
determining initial values for said set of parameters; and
performing an estimation cycle comprising;
receiving a training set having members;
performing recognition on said members using a current set of parameters and said predetermined group of elements;
generating at least one equivalence set comprising recognized members of said training set;
using said equivalence sets and said set of parameters to calculate a target function;
maximizing said target function with respect to said set of parameters;
updating said set of parameters to maximize said target function;
if said set of parameters satisfies a predetermined estimation termination condition, discontinuing said parameter estimation; and
if said set of parameters does not satisfy a predetermined estimation termination condition, performing another estimation cycle;
transcribing said input sequence according to said statistical model having said estimated set of parameters. - View Dependent Claims (94, 95, 96, 97, 98, 99, 100, 101, 102, 103, 104, 105, 106, 107)
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Specification