ruptures
madmom
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| ruptures | madmom | |
|---|---|---|
| 1 | 2 | |
| 1,473 | 1,239 | |
| - | 1.9% | |
| 5.7 | 4.4 | |
| 26 days ago | 5 months ago | |
| Python | Python | |
| BSD 2-clause "Simplified" License | GNU General Public License v3.0 or later |
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ruptures
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[D] Inverse of Event Detection - Temporal Disruption Analysis
For offline CPD I’ve seen projects that use ruptures. In addition to the paper mentioned above this survey also felt quite accessible.
madmom
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Do you know any Onset Detection methods?
There are also online & offline onset detection approaches available as part of the Python madmom library https://github.com/CPJKU/madmom as binaries and Python classes. The methods included in madmom have shown state of the art results in multiple Music Information Retrieval Evaluation eXchange (MIREX) campaigns in recent years. Hope that's useful to you.
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BOXVR song importing. Can this be done outside of being in the game in VR?
In BoxVR's case, they literally use a machine learning model. It's cutting edge tech. Read more about it here: The paper, the code (and a sub-paper)
What are some alternatives?
ssqueezepy - Synchrosqueezing, wavelet transforms, and time-frequency analysis in Python
expression_evaluator - A basic expression evaluator and depth analyzer
python-performance - Repository for the book Fast Python - published by Manning
orbit - A Python package for Bayesian forecasting with object-oriented design and probabilistic models under the hood.
inaSpeechSegmenter - CNN-based audio segmentation toolkit. Allows to detect speech, music, noise and speaker gender. Has been designed for large scale gender equality studies based on speech time per gender.
pywt - PyWavelets - Wavelet Transforms in Python
Sushi - Automatic subtitle shifter based on audio
SincNet - SincNet is a neural architecture for efficiently processing raw audio samples.
audio-reactive-led-strip - :musical_note: :rainbow: Real-time LED strip music visualization using Python and the ESP8266 or Raspberry Pi
omnizart - Omniscient Mozart, being able to transcribe everything in the music, including vocal, drum, chord, beat, instruments, and more.