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Generated January 22, 2018

Pattern recognition using an observable operator model

Patent Number: 6,845,357

Patent Information

Abstract
Data structures, systems, and methods are aspects of pattern recognition using observable operator models (OOMs). OOMs are more efficient than Hidden Markov Models (HMMs). A data structure for an OOM has characteristic events, an initial distribution vector, a probability transition matrix, an occurrence count matrix, and at least one observable operator. System applications include computer systems, cellular phones, wearable computers, home control systems, fire safety or security systems, PDAs, and flight systems. A method of pattern recognition comprises training OOMs, receiving unknown input, computing matching probabilities, selecting the maximum probability, and displaying the match. A method of speech recognition comprises sampling a first input stream, performing a spectral analysis, clustering, training OOMs, and recognizing speech using the OOMs.
Patent Number: 6,845,357
Issue Date: 2005-01-18

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Citations

Patents cited by this patent

Patent Title
6,151,592 Recognition apparatus using neural network, and learning method therefor
6,151,574 Technique for adaptation of hidden markov models for speech recognition
6,052,662 Speech processing using maximum likelihood continuity mapping
5,983,186 Voice-activated interactive speech recognition device and method
5,860,062 Speech recognition apparatus and speech recognition method
5,857,169 Method and system for pattern recognition based on tree organized probability densities

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