document created by: Sandeep Dasari
last updated: 2019, October 28
last updated by: Sandeep
Inspired from Google Experiments' The Infinte Drum Machine, this project seeks to take the idea of 2 Dimensional visualization of higher dimensional audio data. Unlike t-SNE that maps high dimensional STFT data to 2-D/3-D , this project focuses on using simpler musical descriptors or popular music information retreival features like
- Spectral centroid
- RMS
- Spectral Flux
- Attack
- Decay etc.
The reason for simplifying the dimensions is to allow the user to interactively sort a large pool of audio samples forming a general sense for these features as filters of sonic quality. The dataset was parsed and processed to extract features in Python. Later a Principal Component Analysis is run to reduce dimensions and perform a K-Means on the sample library. The results from PCA are sent to Max via OSC for interactive audio plotting of the one-hit samples.
Max 8for visualization and sonoficationpython-oscmatplotlibsklearnessentiapy-dublibrosapandasnumpy
/samplescontains all the 160 one hit acoustic drum kit sample/main.pyis the python file that parses samples and sends PCA co-ordinates to Max/MSP/viz.maxpatcontains the Max patch that receives OSC, plots audio samples and plays them in real time./pca.movis an initial demo video of the application