Recognition of consonant-vowel utterances using Support Vector Machines
نویسندگان
چکیده
In conventional approaches for multi-class pattern recognition using Support Vector Machines (SVMs), each class is discriminated against all the other classes to build an SVM for that class. We propose a close-class-set discrimination method suitable for large class set pattern recognition problems. An SVM is built for each of the 145 ConsonantVowel (CV) classes by discriminating that class against only a small number (about 15) of classes close to it phonetically. The method leads to about 17% reduction in the average number of support vectors per class with a decrease of only 4.4% in the recognition accuracy.
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