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ZENODO
Software . 2018
Data sources: Datacite
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ZENODO
Software . 2018
Data sources: ZENODO
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ZENODO
Software . 2018
Data sources: Datacite
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Fast Python implementation of the Yin algorithm

integration_instructionsResearch softwarekeyboard_double_arrow_right Software 19 Apr 2018Publisher:Zenodo
Authors: Guyot, Patrice;
Code repository: https://github.com/patriceguyot/Yin/tree/v1.1.1

doi: 10.5281/zenodo.1220947 , 10.5281/zenodo.1220272

Fast Python implementation of the Yin algorithm

Abstract

Fast Python implementation of the Yin algorithm: a fundamental frequency estimator. Based on the article: \[1\] De Cheveigné, A., & Kawahara, H. (2002). YIN, a fundamental frequency estimator for speech and music. The Journal of the Acoustical Society of America, 111(4), 1917-1930. All the functions in the code correspond to steps in the article \[1\]. Meanwhile, the difference function has been modify substantially in order to improve speed. Finally, speed has been improved by more than 1000x.

Keywords

audio pitch f0 yin

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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