Digit recognition using wavelet and SVM in Brazilian Portuguese

Abstract

In this paper we used WPT (Wavelet Packet Transform) and neural classifier SVM (Support Vector Machine) to recognize spoken digits from 0 to 9 in Brazilian Portuguese. The main objective this work is to find out the Wavelet mother that better represents the speech signal in Brazilian Portuguese. The results obtained were compared with MFCC (Mel frequency cepstral coefficients). We carried out sixteen experiments with different Wavelets in dependent-case and four experiments in independent-case. The database was recorded in three months with 82 eighteen-to-forty years old male speakers. The SVM was used as a classifier in a “one vs. all” strategy. Best results have been obtained using Wavelets Daubechies 5, Meyer and Coiflet 5. Finally, we used a neural network MLP (Multi Layer Perceptron) in order to improve the SVM results.