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Cognitive Computation
Erschienen in: Cognitive Computation 3/2010

01.09.2010

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

verfasst von: Mohamed Anouar Ben Messaoud, Aïcha Bouzid, Noureddine Ellouze

Erschienen in: Cognitive Computation | Ausgabe 3/2010

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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.
Vorheriger Artikel Phoneme Recognition by Means of a Growing Hierarchical Recurrent Self-Organizing Model Based on Locally Adapting Neighborhood Radii
Nächster Artikel Reducing Features Using Discriminative Common Vectors

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Metadaten
Titel
Autocorrelation of the Speech Multi-Scale Product for Voicing Decision and Pitch Estimation
verfasst von
Mohamed Anouar Ben Messaoud
Aïcha Bouzid
Noureddine Ellouze
Publikationsdatum
01.09.2010
Verlag
Springer-Verlag
Erschienen in
Cognitive Computation / Ausgabe 3/2010
Print ISSN: 1866-9956
Elektronische ISSN: 1866-9964
DOI
https://doi.org/10.1007/s12559-010-9048-1

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EditorialNotes

Non-Linear and Non-Conventional Speech Processing: Alternative Techniques