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calculates rhythm complexity from the entropy of the sub audible spectrum

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rythm_entropy

calculates rhythm complexity from the entropy of the sub audible spectrum. The basic Idea is that the Shannon entropy is a measure for peakyness of a distribution and a simple rhythm would have only one peak and more complex rhythms feature more peaks.

Use the notebook to analyze a YouTube video or better a playlist. Whole albums in one file tend to overestimate the entropy as song length also contributes to higher entropy. Also songs with varying tempos tend to have a very high score despite the rhythm and structure being fairly simple. The value is calculated via Shannon entropy but I wouldn't consider it to be information, as a Fourier spectrum does not satisfy the requirements of a probability distribution.

Some examples values

  • Metronome : 100
  • Techno: 400
  • Indie Rock: 650
  • Funk: 700
  • Jazz: 800
  • Classical music: >1000

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calculates rhythm complexity from the entropy of the sub audible spectrum

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