Instructional notebooks on music information retrieval.
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Updated
Nov 15, 2023 - Jupyter Notebook
Instructional notebooks on music information retrieval.
Music Information Retrieval Basics Notebooks
Results of the paper: Zapata, Jose R.; Gómez, Emilia. "Comparative Evaluation and Combination of Audio Tempo Estimation Approaches", AES 42nd International Conference: Semantic Audio, Ilmenau, Germany. pp. 198 - 207, Jul 2011. in a jupyter notebook
Jupyter notebooks designed for the analysis of sound waves, audio, and music. The notebooks aim to facilitate research and development in Digital Signal Processing (DSP), Music Information Retrieval (MIR), and other sound-related fields. These tools are suitable for AI experts, data scientists, and engineers with a focus on audio signal processing.
This is a docker image that extends the MIR-toolbox-docker docker image. The MIR-toolbox-docker image runs an ipython notebook server with as set of MIR python packages and MTG's music/audio analyis library Essentia. We provide in here a way of to facilitate extending the base image with new requirements.
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