Recognition of Greek Phonemes Using Support Vector Machines

Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3955)


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.


Support Vector Machine Language Model Independent Component Analysis Acoustic Model Phoneme Recognition 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  1. 1.Wire Communications Laboratory, Dept. of Electrical and Computer EngineeringUniversity of PatrasRion, PatrasGreece

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