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| This repository contains a Python package called libf0 which provides open-source implementations for four popular model-based F0-estimation approaches, YIN (Cheveigné & Kawahara, 2002), pYIN (Mauch & Dixon, 2014), an approach inspired by Melodia (Salamon & Gómez, 2012), and SWIPE (Camacho & Harris, 2008). | |
| If you use the libf0 in your research, please consider the following references. | |
| ## References | |
| Sebastian Rosenzweig, Simon Schwär, and Meinard Müller. | |
| [A Python Library for Fundamental Frequency Estimation.](https://archives.ismir.net/ismir2022/latebreaking/000003.pdf) | |
| In Late Breaking Demos of the International Society for Music Information Retrieval Conference (ISMIR), Bengaluru, India, 2022. | |
| Alain de Cheveigné and Hideki Kawahara. | |
| YIN, a fundamental frequency estimator for speech and music. Journal of the Acoustical Society of America (JASA), 111(4):1917–1930, 2002. | |
| Matthias Mauch and Simon Dixon. | |
| pYIN: A fundamental frequency estimator using probabilistic threshold distributions. In IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pages 659–663, Florence, Italy, 2014. | |
| Justin Salamon and Emilia Gómez. | |
| Melody extraction from polyphonic music signals using pitch contour characteristics. IEEE Transactions on Audio, Speech, and Language Processing, 20(6): | |
| 1759–1770, 2012. | |
| Arturo Camacho and John G. Harris. | |
| A sawtooth waveform inspired pitch estimator for speech and music. The Journal of the Acoustical Society of America, 124(3):1638–1652, 2008. | |
| Meinard Müller. Fundamentals of Music Processing – Using Python and Jupyter Notebooks. Springer Verlag, 2nd edition, 2021. ISBN 978-3-030-69807-2. doi: 10.1007/978-3-030-69808-9. | |
| ## Documentation | |
| There is also an API documentation for libf0: | |
| https://groupmm.github.io/libf0 | |
| ## Contributing | |
| We are happy for suggestions and contributions. We would be grateful for either directly contacting us via email (meinard.mueller@audiolabs-erlangen.de) or for creating an issue in our Github repository. Please do not submit a pull request without prior consultation with us. | |
| ## Licence | |
| The code for this toolbox is published under an MIT licence. | |
| ## Acknowledgements | |
| This work was supported by the German Research Foundation (MU 2686/13-1, SCHE 280/20-1). We thank Edgar Suárez and Vojtěch Pešek for helping with the implementations. Furthermore, we thank Fatemeh Eftekhar and Maryam Pirmoradi for testing the toolbox. The International Audio Laboratories Erlangen are a joint institution of the Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU) and Fraunhofer Institute for Integrated Circuits IIS. | |