Training Method for Pattern Classifier Based on the Performance after Adaptation

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概要

• 論文の詳細を見る

• 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.

• 社団法人電子情報通信学会の論文
• 2000-07-25

著者

• Iwahashi Naoto

  Sony Computer Science Labs Inc.

関連論文

• Training Method for Pattern Classifier Based on the Performance after Adaptation

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