Deep Learning for Audio-Based Music Classification and Tagging

Abstract

Over the last decade, music-streaming services have grown dramatically. Pandora, one company in the field, has pioneered and popularized streaming music by successfully deploying the Music Genome Project [1] (https://www.pandora.com/about/mgp) based on human-annotated content analysis. Another company, Spotify, has a catalog of over 40 million songs and over 180 million users as of mid-2018 (https://press.spotify.com/us/about/), making it a leading music service provider worldwide. Giant technology companies such as Apple, Google, and Amazon have also been strengthening their music service platforms. Furthermore, artificial intelligence speakers, such as Amazon Echo, are gaining popularity, providing listeners with a new and easily accessible way to listen to music.

Related

December 2020 | NeuRIPS

Model Selection for Production System via Automated Online Experiments

Zhenwen Dai, Praveen Chandar, Ghazal Fazelnia, Benjamin Carterette, Mounia Lalmas

October 2020 | CIKM

Query Understanding for Surfacing Under-served Music Content

Federico Tomasi, Rishabh Mehrotra, Aasish Pappu, Judith Bütepage, Brian Brost, Hugo Galvão, Mounia Lalmas

September 2020 | RecSys

Contextual and Sequential User Embeddings for Large-Scale Music Recommendation

Casper Hansen, Christian Hansen, Lucas Maystre, Rishabh Mehrotra, Brian Brost, Federico Tomasi, Mounia Lalmas