Cross-synthesis using non-negative Matrix Factorisation (NMF)

NMFMorph uses a technique called Optimal Transport to provide real time interpolation between source and target bases of a BufNMF decomposition. Using Optimal Transport for the spectral interpolation provides richer results than a simple linear interpolation between spectral shapes. Activations from a BufNMF analysis are also provided to activate the interpolated spectral information through time.

If autoassign is set to 1, NMFMorph will determine which bases from source and target best match each other, and will interpolate between the matched pairings. If autoassign is set to 0, NMFMorph will interpolate between bases in the order they have been provided.

Audio Morphing using Matrix Decomposition and Optimal Transport

Paper by Roma, Green, & Tremblay describing the NMFMorph algorithm. (begins on PDF page 165 of the DAFx2020 Proceedings)

Audio Transport: A Generalized Portamento via Optimal Transport

The paper which inspired this implementation

Computational Optimal Transport

For those who really want to get down in the details

Optimal transport: a hidden gem that empowers today’s machine learning

A relatively easy to approach article on applications of optimal transport

Last modified: Tue Aug 23 14 by James Bradbury
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