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An overview of the CATE algorithms for real-time pitch determination

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Abstract

In this paper, we present a recent algorithm for pitch detection based on an implicit circular autocorrelation of the glottal excitation signal. This algorithm operates in real time without the use of any post-processing technique. This article focuses on the correction of the pitch contours estimated and on the reduction in classification errors in speech signals using simple voicing decision techniques. To evaluate the performance of our algorithms, we used the Bagshaw and Keele databases. We show in this study that the sum of the percentage of the unvoiced errors and the percentage of the voiced errors, for the male Bagshaw corpus, reaches a very good score of 14.67. For the female corpus, our results are also competitive compared to other algorithms using the same database. Concerning the Keele database, we succeed to obtain very good gross pitch error, voicing decision error and F0 frame error rates, respectively, 0.44, 0.65 and 1.55 % in the whole corpus.

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Authors and Affiliations

  1. LRIT Laboratory, Unit Associated to CNRST, URAC 29, Faculty of Sciences, Univrsité Mohammed V-Agdal, Avenue Ibn Batouta, B.P. 1014, Rabat, Morocco

    Fadoua Bahja & Driss Aboutajdine

  2. LORIA, B.P. 239, Vandoeuvre-lès-Nancy, France

    Joseph Di Martino

  3. INPT, Avenue Allal Al Fassi, Madinat Al Irfane, Rabat, Morocco

    Elhassan Ibn Elhaj

Authors
  1. Fadoua Bahja
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  2. Joseph Di Martino
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  3. Elhassan Ibn Elhaj
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  4. Driss Aboutajdine
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Correspondence to Fadoua Bahja.

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Bahja, F., Di Martino, J., Ibn Elhaj, E. et al. An overview of the CATE algorithms for real-time pitch determination. SIViP 9, 589–599 (2015). https://doi.org/10.1007/s11760-013-0488-4

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