Data Driven Audio Signal Processing - A Tutorial with Computational Examples
This tutorial accompanies the lecture Data Driven Audio Signal Processing. The lecture and the tutorial are designed for International Standard Classification of Education (ISCED) level 7 (Master, in total 6 ECTS credits).
Jupyter notebooks can be accessed via the services
- dynamic version using mybinder: https://mybinder.org/v2/gh/spatialaudio/data-driven-audio-signal-processing-exercise/dev?labpath=index.ipynb
- static version using nbviewer: https://nbviewer.org/github/spatialaudio/data-driven-audio-signal-processing-exercise/blob/dev/index.ipynb
- sources (tex, ipynb) at: https://github.com/spatialaudio/data-driven-audio-signal-processing-exercise
- v0.1 for winter term 2021/22, initial version
- v0.2 for winter term 2022/23
- v0.3 for winter term 2023/24, many beamer tex slides added, CI
- v0.4 winter term 2024/25, smaller mods due to API changes, PCA example on exam grades, slides
- v0.5 winter term 2025/26, TBD
- the default branch of the repository is
devand this is used for development - the
devbranch contains notebooks with cleared outputs for convenient diff handling - the
mainbranch contains notebooks with rendered outputs, which is maintained from time to time - do not rely on
mainbranch as this is hard reset from time to time - probably in future we rename
mainto somewhat less confusing
- the
pyproject.tomlcontains the project info - assuming we use uv for Python, packaging and environment handling a dedicated environment can be cerated with
uv sync
- University of Rostock:
- Frank Schultz, concept, coding
- Sascha Spors, concept
Please cite this open educational resource (OER) project as
Frank Schultz, Data Driven Audio Signal Processing - A Tutorial Featuring Computational Examples, University of Rostock ideally with relevant file(s), github URL, commit number and/or version tag, year.
- Creative Commons Attribution 4.0 International License (CC BY 4.0) for text/graphics
- MIT License for software