Pattern recognition device, pattern recognition method, and computer program product

A pattern recognition method executed by a pattern recognition device, comprising:

• dividing an input signal into a plurality of elements by the pattern recognition device;
• converting the divided elements into feature vectors having the same dimensionality, and generating a set of feature vectors by the pattern recognition device;
• and
• evaluating the set of feature vectors using a recognition dictionary, and outputting a recognition result representing a class or a set of classes to which the input signal belongs by the pattern recognition device, wherein
• the recognition dictionary includes models corresponding to respective classes,
• the models each include sub-models each corresponding to one of possible division patterns in which a signal to be classified into a class corresponding to the model can be divided into a plurality of elements,
• each sub-model has a state corresponding to each element divided based on a division pattern corresponding to the sub-model, the state being expressed by a function of labels representing a feature vector and the state, and
• a label expressing a model including a sub-model conforming to the set of feature vectors, or a set of labels expressing a set of models including sub-models conforming to the set of feature vectors is output as the recognition result at the outputting.

A computer program product comprising a computer-readable medium including programmed instructions, the instructions causing a computer to implement:

• a function of a division unit configured to divide an input signal into a plurality of elements;
• a function of a feature extracting unit configured to convert the divided elements into feature vectors having the same dimensionality, and generate a set of feature vectors;
• and
• a function of a recognition unit configured to evaluate the set of feature vectors using a recognition dictionary, and output a recognition result representing a class or a set of classes to which the input signal belongs, wherein
• the recognition dictionary includes models corresponding to respective classes,
• the models each include sub-models each corresponding to one of possible division patterns in which a signal to be classified into a class corresponding to the model can be divided into a plurality of elements,
• each sub-model has a state corresponding to each element divided based on a division pattern corresponding to the sub-model, the state being expressed by a function of labels representing a feature vector and the state, and
• the recognition unit outputs, as the recognition result, a label expressing a model including a sub-model conforming to the set of feature vectors, or a set of labels expressing a set of models including sub-models conforming to the set of feature vectors.