Development of a MFCC-SVM Based Turkish Speech Recognition System

Abstract

In this study, a SVM-MFCC based Turkish Speech Recognition system is devoloped. In the structure, Mel Frequency Cepstral Coefficients (MFCC) are used for feature extraction and Support Vector Machines(SVM) are used for classification of the phonemes. Three more phoneme recognition methods are applied to same dataset and their perfomance is compared. The applied methods are the combination of the Linear Prediction Cepstral Coefficients (LPCC), which is a commonly used method of feature extraction and Hidden Markov Method (HMM) which is a known classification method. The applied feature extraction and classification methods has been selected due to phoneme-based property of the Turkish language.