The FMP notebooks are a collection of educational material for teaching and learning Fundamentals of Music Processing (FMP) with a particular focus on the audio domain. Covering well-established topics in Music Information Retrieval (MIR) as motivating application scenarios, the FMP notebooks provide detailed textbook-like explanations of central techniques and algorithms in combination with Python code examples that illustrate how to implement the theory. All components including the introductions of MIR scenarios, illustrations, sound examples, technical concepts, mathematical details, and code examples are integrated into a consistent and comprehensive framework based on Jupyter notebooks. The FMP notebooks are suited for studying the theory and practice, for generating educational material for lectures, as well as for providing baseline implementations for many MIR tasks, thus addressing students, teachers, and researchers.
The text and figures of these notebooks are licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License (see the file LICENSE ). The Python package libfmp (i.e., the content of the directory libfmp ) is licensed under the MIT license (see file libfmp_LICENSE ) and is available at GitHub. As for the audio material, the respective original licenses apply. This site contains material (text passages, figures) from the book Fundamentals of Music Processing. If you use code or material from this site, please give reference to this book (e.g. Figure 1.1 from [Müller, FMP, Springer 2021]). If you publish results obtained or using these Python notebooks, please consider the following references:
Fundamentals of Music Processing – Using Python and Jupyter Notebooks. 2nd edition, Springer Verlag, 2021.
Bibtex Link Meinard Müller:2nd edition, Springer Verlag, 2021.
FMP Notebooks: Educational Material for Teaching and Learning Fundamentals of Music Processing. Proceedings of the International Conference on Music Information Retrieval (ISMIR), Delft, The Netherlands, 2019.
Bibtex PDF Meinard Müller and Frank Zalkow:Proceedings of the International Conference on Music Information Retrieval (ISMIR), Delft, The Netherlands, 2019.
libfmp: A Python Package for Fundamentals of Music Processing. The Journal of Open Source Software (JOSS), 6(63), 2021.
Bibtex PDF GitHub Meinard Müller and Frank Zalkow:The Journal of Open Source Software (JOSS), 6(63), 2021.
An Educational Guide Through the FMP Notebooks for Teaching and Learning Fundamentals of Music Processing. Signals, 2(2):245-285, 2021.
Bibtex PDF Meinard Müller:Signals, 2(2):245-285, 2021.
The FMP notebooks are maintained by Meinard Müller. For comments, please email meinard.mueller@audiolabs-erlangen.de. I am grateful for feedback and suggestions.