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Speech recognition of thai digits using modified cross-correlation neural network
Author(s)
Klomiam, Narodom
Date Issued
December 1, 2004
Type
Conference Paper
Abstract
In this paper, Modified Cross-Correlation Neural Network (MCCNN), which is an extension of Cross-Correlation Neural Network (CCNN) [1], is proposed. Unlike the CCNN, which utilizes the normalized cross-correlation at zero lag as a choice function to determine the winning cluster node, MCCNN uses the maximum of the normalized cross-correlation instead. In this work, spoken Thai digits (0-9) are used as the experimental data. The performance of MCCNN, CCNN and other two well-known algorithms, Back-propagation and Fuzzy ARTMAP, are compared. The results show that MCCNN has the best performance with respect to the recognition rate.
Citation
Proceedings of the IASTED International Conference Applied Informatics, 678-682, 2004