Recognition of greek phonemes using support vector machines

Authors:
Iosif Mporas;Todor Ganchev;Panagiotis Zervas;Nikos Fakotakis
Affiliations:
Wire Communications Laboratory, Dept. of Electrical and Computer Engineering, University of Patras, Rion, Patras, Greece;Wire Communications Laboratory, Dept. of Electrical and Computer Engineering, University of Patras, Rion, Patras, Greece;Wire Communications Laboratory, Dept. of Electrical and Computer Engineering, University of Patras, Rion, Patras, Greece;Wire Communications Laboratory, Dept. of Electrical and Computer Engineering, University of Patras, Rion, Patras, Greece
Venue:
SETN'06 Proceedings of the 4th Helenic conference on Advances in Artificial Intelligence
Year:
2006

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Abstract

In the present work we study the applicability of Support Vector Machines (SVMs) on the phoneme recognition task. Specifically, the Least Squares version of the algorithm (LS-SVM) is employed in recognition of the Greek phonemes in the framework of telephone-driven voice-enabled information service. The N-best candidate phonemes are identified and consequently feed to the speech and language recognition components. In a comparative evaluation of various classification methods, the SVM-based phoneme recognizer demonstrated a superior performance. Recognition rate of 74.2% was achieved from the N-best list, for N=5, prior to applying the language model.