[OC] Thirteen examples of audio files, analyzed (using Python) for nine different metrics; including timbre, loudness and tempo. That data is then visualized using D3 as overlapping line graphs, demoing evolution over time.
[OC] Thirteen examples of audio files, analyzed (using Python) for nine different metrics; including timbre, loudness and tempo. That data is then visualized using D3 as overlapping line graphs, demoing evolution over time.
In total [the program that I wrote](https://github.com/devbret/detailed-audio-analysis) measures onsets, timbre, loudness, chroma, tempo, spectral centroid, spectral bandwidth, zero crossing and spectral contrast. These metrics are analyzed using numerous Python libraries, which al come together as a JSON file. That is then imported/uploaded into the D3 visualization script, which you see thirteen examples of here.
The audio files that you see displayed in the image attached to this post are some of the [original sound effects that I have made](https://freesound.org/people/bernhoftbret/) over the past couple of years.
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In total [the program that I wrote](https://github.com/devbret/detailed-audio-analysis) measures onsets, timbre, loudness, chroma, tempo, spectral centroid, spectral bandwidth, zero crossing and spectral contrast. These metrics are analyzed using numerous Python libraries, which al come together as a JSON file. That is then imported/uploaded into the D3 visualization script, which you see thirteen examples of here.
The audio files that you see displayed in the image attached to this post are some of the [original sound effects that I have made](https://freesound.org/people/bernhoftbret/) over the past couple of years.