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Found 3 papers, 2 papers with code
Timbre-Trap: A Low-Resource Framework for Instrument-Agnostic Music Transcription
Several works have explored multi-instrument transcription as a means to bolster the performance of models on low-resource tasks, but these methods face the same data availability issues.
Music Mixing Style Transfer: A Contrastive Learning Approach to Disentangle Audio Effects
We propose an end-to-end music mixing style transfer system that converts the mixing style of an input multitrack to that of a reference song.
Automatic music mixing with deep learning and out-of-domain data
Music mixing traditionally involves recording instruments in the form of clean, individual tracks and blending them into a final mixture using audio effects and expert knowledge (e. g., a mixing engineer).
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