Spectral multi-scale product analysis for pitch estimation from noisy speech signal

Authors:
Mohamed Anouar Ben Messaoud;Aïcha Bouzid;Noureddine Ellouze
Affiliations:
Department of Electrical Engineering, National School of Engineers of Tunis, Tunis, Tunisia;Department of Electrical Engineering, National School of Engineers of Tunis, Tunis, Tunisia;Department of Electrical Engineering, National School of Engineers of Tunis, Tunis, Tunisia
Venue:
NOLISP'09 Proceedings of the 2009 international conference on Advances in Nonlinear Speech Processing
Year:
2009

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Abstract

In this work, we present an algorithm for estimating the fundamental frequency in speech signals. Our approach is based on the spectral multi-scale product analysis. It consists of operating a short Fourier transform on the speech multi-scale product. The multi-scale product is based on making the product of the speech wavelet transform coefficients at three successive dyadic scales. The wavelet used is the quadratic spline function with a support of 0.8 ms. We estimate the pitch for each time frame based on its multi-scale product harmonic structure. We evaluate our approach on the Keele database. Experimental results show the effectiveness of our method presenting a good performance surpassing other algorithms. Besides, the proposed approach is robust for noisy speech.