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In Out-of Vocabulary Rejection Algorithm by Measure of Normalized improvement using Optimization of Gaussian Model Confidence

  • Journal of The Korea Society of Computer and Information
  • Abbr : JKSCI
  • 2010, 15(12), pp.125-132
  • Publisher : The Korean Society Of Computer And Information
  • Research Area : Engineering > Computer Science

안찬식 1 Sang-Yeob Oh 2

1광운대학교
2경원대학교

Accredited

ABSTRACT

In vocabulary recognition has unseen tri-phone appeared when recognition training. This system has not been created beginning estimation figure of model parameter. It's bad points could not be created that model for phoneme data. Therefore it's could not be secured accuracy of Gaussian model. To improve suggested Gaussian model to optimized method of model parameter using probability distribution. To improved of confidence that Gaussian model to optimized of probability distribution to offer by accuracy and to support searching of phoneme data. This paper suggested system performance comparison as a result of recognition improve represent 1.7% by out-of vocabulary rejection algorithm using normalization confidence.

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