Douglas Eck, Google, USA: Music recommendation and discovery at scale

Please note that this lecture takes place on a TUESDAY, which differs from the usual Distinguished Lecture schedule.

The lecture will take place in Tanna Schulich Hall, followed by a wine and cheese reception in room A832 & A833 (8th floor of the New Music Building).


ABSTRACT: 

I will discuss recent work done at Google to tackle the problem of music recommendation in a streaming music service.  I'll look at some strategies for using audio features as a means to improve quality and to go deep into the long tail. I'll also look at embeddings-based methods for collaborative filtering.  Finally I'll discuss the use of Knowledge Graph as a means for providing structured data about the world of music. An overarching theme in the talk is, "What do listeners actually want from a music streaming service?" I don't have a complete answer for this, but think it's worth talking about, especially since it motivates collaborations across domains relevant for CIRMMT.  Though I'll address some of the technical and algorithmic details involved in building a music recommendation system, the talk is geared for a general audience.

 

ABOUT DOUGLAS ECK:

Staff Research Scientist, Google, Mountain View

Douglas leads a team carrying out research in music recommendations, search and discovery. Before coming to Google, Douglas was an associate professor in Computer Science at the University of Montreal where he worked with the LISA machine learning lab, the Centre for Research in Brain Music and Sound (BRAMS) and the Centre for Interdisciplinary Research in Music Media and Technology (CIRMMT).

deck[AT]google.com

 

VIDEO ARCHIVE - DOUGLAS ECK

APA video citation:

Eck, D. (2014, October 30). Music recommendation and discovery at scale -
CIRMMT Distinguished Lectures in the Science and Technology of Music. [Video file].
Retrieved from https://www.youtube.com/watch?v=GAzVZOZe2f8