Music Information Retrieval at Spotify and the Future of ML Tooling with Andreas Jansson of Replicate

Machine Learning Engineered

Dec 15 2020 • 1 hr 33 mins

Andreas Jansson is the co-founder of Replicate, a version control tool for machine learning. He holds a PhD from City University of London in Music Informatics and was previously a machine learning engineer at Spotify, researching and applying algorithms for music information retrieval. Learn more about Andreas: ( ( Every Thursday I send out the most useful things I’ve learned, curated specifically for the busy machine learning engineer. Sign up here: ( Follow Charlie on Twitter: ( Subscribe to ML Engineered: ( Comments? Questions? Submit them here: ( Take the Giving What We Can Pledge: ( Timestamps: 02:30 Andreas Jansson 07:30 Overview of music information retrieval (MIR) 13:30 Why use spectrograms and not raw audio? 19:55 The potential for transformers in MIR 22:45 Most exciting applications for ML in MIR 29:20 Challenges in putting ML into production 36:45 What Andreas imagines for the future of ML tools 41:45 Why he's building a tool for ML version control ( ( 52:55 What Replicate enables via integration or as a platform 01:02:55 Learnings from doing customer discovery for Replicate 01:14:10 "Github for ML models and data" 01:22:30 Rapid fire questions Links: (WaveNet: a generative model for raw audio) (Singing Voice Separation with Deep U-Net CNNs) (Joint Singing Voice Separation and F0 Estimation with Deep U-Net Architectures) (arXiv Vanity) (Replicate) (Replicate's Discord)