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. © Springer-Verlag Berlin Heidelberg 2006.
CITATION STYLE
Mporas, I., Ganchev, T., Zervas, P., & Fakotakis, N. (2006). Recognition of Greek phonemes using support vector machines. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 3955 LNAI, pp. 290–300). Springer Verlag. https://doi.org/10.1007/11752912_30
Mendeley helps you to discover research relevant for your work.