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Published in:
2006 | OriginalPaper | Chapter
Recognition of Greek Phonemes Using Support Vector Machines
Authors : Iosif Mporas, Todor Ganchev, Panagiotis Zervas, Nikos Fakotakis
Published in: Advances in Artificial Intelligence
Publisher: Springer Berlin Heidelberg
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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.