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Generating music in the waveform domain – Sander Dieleman

sander.ai · 9,829 words · saved by 2 readers

In November last year, I co-presented a tutorial on waveform-based music processing with deep learning with Jordi Pons and Jongpil Lee at ISMIR 2019. Jongpil and Jordi talked about music classification and source separation respectively, and I presented the last part of the tutorial, on music generation in the waveform domain. It was very well received, so I’ve decided to write it up in the form of a blog post. ISMIR used to be my home conference when I was a PhD student working on music information retrieval, so it was great to be back for the first time in five years. With about 450 attendees (the largest edition yet), it made for a very different experience than what I’m used to with machine learning conferences like ICML, NeurIPS and ICLR, whose audiences tend to number in the thousands these days. Our tutorial on the first day of the conference gave rise to plenty of interesting questions and discussions throughout, which inspired me to write some of these things down and hopefull

In November last year, I co-presented a tutorial on waveform-based music processing with deep learning with Jordi Pons and Jongpil Lee at ISMIR 2019 . Jongpil and Jordi talked about music classification and source separation respectively, and I presented the last part of the tutorial, on music generation in the waveform domain. It was very well received, so I’ve decided to write it up in the form of a blog post. ISMIR used to be my home conference when I was a PhD student working on music information retrieval, so it was great to be back for the first time in five years. With about 450 attende

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