Speech recognition of thai digits using modified cross-correlation neural network

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dc.contributor.authorThammano, Arit
dc.contributor.authorKlomiam, Narodom
dc.date.accessioned2026-08-06T09:52:56Z
dc.date.available2026-08-06T09:52:56Z
dc.date.issued2004-12-01
dc.description.abstractIn 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.
dc.identifier.citationProceedings of the IASTED International Conference Applied Informatics, 678-682, 2004
dc.identifier.other2-s2.0-11144298020
dc.identifier.urihttps://dspace.kmitl.ac.th/handle/123456789/948
dc.sourceProceedings of the IASTED International Conference Applied Informatics
dc.subjectClassification
dc.subjectCross-correlation
dc.subjectData Mining
dc.subjectNeural Network
dc.subjectSpeech recognition
dc.titleSpeech recognition of thai digits using modified cross-correlation neural network
dc.typeConference Paper

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