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Vocabulary Recognition Model using a convergence of Likelihood Principla Bayesian methode and Bhattacharyya Distance Measurement based on Vector Model
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  • Journal title : Journal of Digital Convergence
  • Volume 13, Issue 11,  2015, pp.165-170
  • Publisher : The Society of Digital Policy and Management
  • DOI : 10.14400/JDC.2015.13.11.165
 Title & Authors
Vocabulary Recognition Model using a convergence of Likelihood Principla Bayesian methode and Bhattacharyya Distance Measurement based on Vector Model
Oh, Sang-Yeob;
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 Abstract
The Vocabulary Recognition System made by recognizing the standard vocabulary is seen as a decline of recognition when out of the standard or similar words. The vector values of the existing system to the model created by configuring the database was used in the recognition vocabulary. The model to be formed during the search for the recognition vocabulary is recognizable because there is a disadvantage not configured with a database. In this paper, it induced to recognize the vector model is formed by the search and configuration using a Bayesian model recognizes the Bhattacharyya distance measurement based on the vector model, by applying the Wiener filter improves the recognition rate. The result of Convergence of two method's are improved reliability experiments for distance measurement. Using a proposed measurement are compared to the conventional method exhibited a performance of 98.2%.
 Keywords
Bhattacharyya Algorithm;Distance Measurement Method;Bayesian Algorithm;Recognition Model;Recognition Improve;
 Language
Korean
 Cited by
 References
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