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.
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Ben Messaoud, M.A., Bouzid, A., Ellouze, N. (2010). Spectral Multi-scale Product Analysis for Pitch Estimation from Noisy Speech Signal. In: Solé-Casals, J., Zaiats, V. (eds) Advances in Nonlinear Speech Processing. NOLISP 2009. Lecture Notes in Computer Science(), vol 5933. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-11509-7_13
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DOI: https://doi.org/10.1007/978-3-642-11509-7_13
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-11508-0
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