Optimal Wavelet for Bangla Vowel Synthesis

Conventional methods uses Fourier Transform (FT) for Bangla vowel synthesis which has resolution problem. In order to produce better accuracy, we attempted Wavelet Transform (WT) with several wavelet families for analyzing and synthesizing the seven Bangla vowels. The parameters for performance evaluation for selecting optimal wavelet for Bangla phoneme synthesis are normalized root mean square error (NRMSE), signal to noise ratio (SNR), peak signal to noise ratio (PSNR), and retained energy (RE) of the first few coefficients of the first approximation decomposition. Our work is centered on the following wavelet families Daubechies, Coiflet, Symmlet, Biorthogonal and Reverse Biorthogonal. It is observed from our study that symmlet8(sym8) wavelet at decomposition level 5, stores more than 98% of the energy in the first few approximation coefficient with moderate SNR, PSNR and reproduces the signal with lowest NRMSE.