Pattern recognition system and method
First Claim
1. A pattern recognition system comprising:
- means for providing a test feature set of a generally noisy input signal characterizing at least a portion of an input pattern contained within said input signal;
means for providing a plurality of reference feature sets of reference templates produced in a quiet environment;
means for providing a background noise feature set of background noise present in said input signal;
a template adapter for producing adapted reference templates from said test feature set, said background noise feature set and said reference feature sets; and
a global scoring unit for determining match scores defining the match between each of said adapted reference templates and said test feature set,wherein said feature sets are autocorrelation feature sets and said template adapter includes;
means for raising the gain level of a reference feature set to the value of the difference of the average energy of said test feature set and the average energy of said background noise feature set; and
means for adjusting said gain-raised reference feature set by adding to it said background noise feature set thereby to create said adapted reference templates.
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Abstract
A pattern recognition system and method is disclosed. The method includes the steps of a) providing a noisy test feature set of the input signal, a plurality of reference feature sets of reference templates produced in a quiet environment, and a background noise feature set of background noise present in the input signal, b) producing adapted reference templates from the test feature set, the background noise feature set and the reference feature sets and c) determining match scores defining the match between each of the adapted reference templates and the test feature set. The method can also include adapting the scores before accepting a score as the result. The system and method are described for both Hidden Markov Model (HMM) and Dynamic Time Warping (DTW) scoring units. The system performs the steps of the method.
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Citations
18 Claims
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1. A pattern recognition system comprising:
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means for providing a test feature set of a generally noisy input signal characterizing at least a portion of an input pattern contained within said input signal; means for providing a plurality of reference feature sets of reference templates produced in a quiet environment; means for providing a background noise feature set of background noise present in said input signal; a template adapter for producing adapted reference templates from said test feature set, said background noise feature set and said reference feature sets; and a global scoring unit for determining match scores defining the match between each of said adapted reference templates and said test feature set, wherein said feature sets are autocorrelation feature sets and said template adapter includes; means for raising the gain level of a reference feature set to the value of the difference of the average energy of said test feature set and the average energy of said background noise feature set; and means for adjusting said gain-raised reference feature set by adding to it said background noise feature set thereby to create said adapted reference templates. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9)
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10. A method for pattern recognition, the method comprising the steps of:
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providing a test feature set of a generally noisy input signal characterizing at least a portion of an input pattern contained within said input signal; providing a plurality of reference feature sets of reference templates produced in a quiet environment; providing a background noise feature set of background noise present in said input signal; producing adapted reference templates from said test feature set, said background noise feature set and said reference feature sets; and determining match scores defining the match between each of said adapted reference templates and said test feature set wherein said feature sets are autocorrelation feature sets and said step of producing includes the steps of; raising the gain level of a reference feature set to the value of the difference of the average energy of said test feature set and the average energy of said background noise feature set; and adjusting said gain-raised reference feature set by adding to it said background noise feature set thereby to create said adapted reference templates. - View Dependent Claims (11, 12, 13, 14, 15, 16, 17, 18)
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Specification