Training Method for Pattern Classifier Based on the Performance after Adaptation

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Author(s)

Abstract

This paper describes a method for training a pattern classifier that will perform well after it has been adapted to changes in input conditions. Considering the adaptation methods which are based on the transformation of classifier parameters, we formulate the problem of optimizing classifiers, and propose a method for training them. In the proposed training method, the classifier is trained while the adaptation is being carried out. The objective function for the training is given based on the recognition performance obtained by the adapted classifier. The utility of the proposed training method is demonstrated by experiments in a five-class Japanese vowel pattern recognition task with speaker adaptation.

Journal

  • IEICE transactions on information and systems

    IEICE transactions on information and systems 83(7), 1560-1566, 2000-07-25

    The Institute of Electronics, Information and Communication Engineers

References:  16

Codes

  • NII Article ID (NAID)
    110003210347
  • NII NACSIS-CAT ID (NCID)
    AA10826272
  • Text Lang
    ENG
  • Article Type
    ART
  • ISSN
    09168532
  • Data Source
    CJP  NII-ELS 
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