Speaker Identification System for Hindi And Marathi Languages using Wavelet and Support Vector Machine

Abstract

In this paper, a speaker identification system using speech processing for Hindi and Marathi languages is developed. Database of common words between Hindi and Marathi languages whose script is common but pronunciation is different is created. Here feature extraction is performed by using Wavelet Packet Decomposition (WPD) and classification is performed by using Support Vector Machine (SVM). As compared to the conventional feature extraction techniques wavelet transform is very much suitable for processing speech signals which are non-stationary in nature because of its efficient time frequency localizations and multi-resolution characteristics. Also SVM is well suitable for addressing speaker identification task. Recognition accuracy of 99.77% is obtained whereas real time recognition accuracy of 84.66% is obtained in identical condition using this hybrid architecture of WPD and SVM. In noisy conditions recognition accuracy of 60% is obtained.
DOI: 10.17762/ijritcc2321-8169.160494