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Autocorrelation of the Speech Multi-Scale Product for Voicing Decision and Pitch Estimation

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Abstract

In this work, we present an algorithm for voiced/unvoiced decision and pitch estimation from speech signals. Our approach is based on classifying the peaks provided by the autocorrelation of 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 autocorrelation function of the multi-scale product is calculated over frames of a specific length. The experimental results show the robustness and the effectiveness of our approach. Besides, the proposed method outperforms some existing algorithms in a clean and noisy environment.

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Acknowledgments

The authors are very grateful to Alain de Cheveigné for providing the fundamental frequency estimation software (Yin algorithm).

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Authors and Affiliations

  1. Department of Electrical Engineering, Tunis El Manar University, ENIT, BP. 37 Le Belvédère, 1002, Tunis, Tunisia

    Mohamed Anouar Ben Messaoud, Aïcha Bouzid & Noureddine Ellouze

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  1. Mohamed Anouar Ben Messaoud
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  2. Aïcha Bouzid
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  3. Noureddine Ellouze
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Correspondence to Mohamed Anouar Ben Messaoud.

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Ben Messaoud, M.A., Bouzid, A. & Ellouze, N. Autocorrelation of the Speech Multi-Scale Product for Voicing Decision and Pitch Estimation. Cogn Comput 2, 151–159 (2010). https://doi.org/10.1007/s12559-010-9048-1

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  • DOI: https://doi.org/10.1007/s12559-010-9048-1

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