Tutorials

Music Recommendation and Discovery Revisited

by Òscar Celma (BMAT) and Paul Lamere (The Echo Nest)

The world of music is changing rapidly. We are now just a few clicks away from being able to listen to nearly any song that has ever been recorded. This easy access to a nearly endless supply of music is changing how we explore, discover, share and experience music.
As the world of online music grows, music recommendation and discovery tools become an increasingly important way for music listeners to engage with music. Commercial recommenders such as Last.fm, iTunes Genius and Pandora have enjoyed commercial and critical success. But how well do these systems really work? How good are the recommendations? How far into the “long tail” do these recommenders reach?
In this tutorial we look at the current state-of-the-art in music recommendation and discovery. We examine current commercial and research systems, focusing on the advantages and the disadvantages of the various recommendation strategies. We look at some of the challenges in building music recommenders and we explore some of the novel techniques that are being used to improve future music recommendation and discovery systems.

About the Speakers

Òscar Celma is the Chief Innovation Officer at Barcelona Music and Audio Technologies (BMAT). In 2008, Òscar obtained his Ph.D. in Computer Science and Digital Communication, in the Pompeu Fabra University (Barcelona, Spain). Òscar has a book published by Springer, titled “Music Recommendation and Discovery: The Long Tail, Long Fail and Long Play in the Music Digital Age” (2010). He holds 2 patents (US2003009344 and JP2003323188, 2002) from his work on the Vocaloid system, a singing voice-synthesizer bought by Yamaha in 2004.

Paul Lamere is the Director of Developer Platform for The Echo Nest, a music intelligence company located in Boston. Paul is interested in using technology to help people explore for new and interesting music. He is active in both the music information retrieval and the recommender systems research communities. Paul authors a popular blog on music technology at MusicMachinery.com.