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Miscellaneous <a href="https://www.python.org/">Python</a> code.
<li><a href="https://gitlab.jyu.fi/juigmend/python-miscellaneous/-/blob/main/audio_MIR_DEMO.ipynb">Audio and MIR</a> (Jupyter notebook) Load audio, extract chroma (keys), and perform segmentation with parametric clustering. </li>
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<li><a href="https://gitlab.jyu.fi/juigmend/python-miscellaneous/-/blob/main/one_vs_others_DEMO.ipynb">One vs. Others</a> (Jupyter notebook) Shows how the Dynamic Time Warping minimum-warp optimal path could be used to assess anticipation or delay of one moving body relative to other moving bodies.</li>
<li><a href="https://gitlab.jyu.fi/juigmend/python-miscellaneous/-/blob/main/dtw_minwarp_DEMO.ipynb">DTW, Minimum-Warp Path, and Pointwise Warp</a> (Jupyter notebook) Two methods for the Dynamic Time Warping algorithm: a library function, and a procedural script. Also algorithms to reduce the time-warping of the optimal path and to get its pointwise warp.</li>
<li><a href="https://gitlab.jyu.fi/juigmend/python-miscellaneous/-/blob/main/novelty_DEMO.py">Novelty</a>
Shows the computation of a novelty score comparing the methods 'offline' (Foote, 2000) and 'online' (Schätti, 2007). </li>