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Converting Source Separation Models to ONNX for Real Time Usage in DJ Software - Anmol Mishra - ADC 2025
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Demucs v4 is a state-of-the-art open-source music source separation model developed by Alexandre Défossez. While it provides exceptional quality in separating audio into stems, it is currently implemented in PyTorch and therefore cannot be used directly in C++ applications or run efficiently on hardware accelerators through ONNX Runtime. Exporting the model to ONNX allows developers to integrate stem separation directly into their platforms, opening up use cases like live stem manipulation, AI-assisted mixing, and educational visualization tools. Through this talk where I demonstrate exporting, deploying and evaluating the exported model, I want to provide a reference for further integration into audio applications.
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Slides: https://audiodeveloperconference.b-cdn.net/wp-content/uploads/2025/07/Anmol-Mishra-ADC25-Demucs-Talk-QR.pdf
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Anmol Mishra
Anmol is a Research Assistant at the Music Technology Group (MTG) and a masters student at UPF Barcelona, working on expressive rhythms generation with flow based diffusion models. Previously he worked as a Machine Learning Research Engineer at Samsung’s Computer Vision Group in Seoul. Prior to that, he earned his Bachelors in Computer Science from IIT Bombay. He's been performing as a DJ at clubs and festivals in Seoul and Barcelona.
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Streamed & Edited by Digital Medium Ltd: https://online.digital-medium.co.uk
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Organized and produced by JUCE: https://juce.com/
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Special thanks to the ADC25 Team:
Sophie Carus
Derek Heimlich
Andrew Kirk
Bobby Lombardi
Tom Poole
Ralph Richbourg
Jim Roper
Jonathan Roper
Prashant Mishra
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