A comparative study of pitch extraction algorithms on a large variety of singing sounds

Onur Babacan 1, * Thomas Drugman 1 Nicolas D'Alessandro 1 Nathalie Henrich 2 Thierry Dutoit 1
* Auteur correspondant
2 GIPSA-SLD - SLD
GIPSA-DPC - Département Parole et Cognition
Abstract : The problem of pitch tracking has been extensively studied in the speech research community. The goal of this paper is to investigate how these techniques should be adapted to singing voice analysis, and to provide a comparative evaluation of the most representative state-of-the-art approaches. This study is carried out on a large database of annotated singing sounds with aligned EGG recordings, comprising a variety of singer categories and singing exercises. The algorithmic performance is assessed according to the ability to detect voicing boundaries and to accurately estimate pitch contour. First, we evaluate the usefulness of adapting existing methods to singing voice analysis. Then we compare the accuracy of several pitchextraction algorithms, depending on singer category and laryngeal mechanism. Finally, we analyze their robustness to reverberation.
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Onur Babacan, Thomas Drugman, Nicolas D'Alessandro, Nathalie Henrich, Thierry Dutoit. A comparative study of pitch extraction algorithms on a large variety of singing sounds. 38th International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2013), May 2013, Vancouver, Canada. ICASSP 2013 - Proceedings, pp.1-5, 2013. 〈hal-00923967〉

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