Tutorial AM 1 (10:00-13:00): MIR at the Scale of the Web
by Malcolm Slaney (Yahoo! Research), and Michael Casey (Dartmouth College)
Abstract
In the last couple of years we have received access to music databases with millions of songs. This massive change in the amount of data available to researchers is changing the face of Music Information Retrieval. [...]
The Problem with Music: Modeling Distance Distributions of Large Music Collection.
Talk at Dartmouth Computer Science Colloquium
Wednesday 21st Januray 2009, Silsby Room 028 (*note location change*), Dartmouth College
Talk Slides
Abstract: Recently, a number of piano recordings by different artists were found in a classical music catalog that exhibited a striking resemblance to each other. Could this [...]
Social Playlists and Bottleneck Measurements: Exploiting Musician Social Graphs Using Content-Based Dissimilarity and Pairwise Maximum Flow Values
Ben Fields, Kurt Jacobson, Christophe Rhodes and Michael Casey
International Conference on Music Information Retrieval (ISMIR), Philadelphia, Sep., 2008
Paper 209 [PDF]
We have sampled the artist social network of Myspace and to it applied the pairwise relational connectivity measure Minimum [...]
Michael Casey, Michela Magas, Christophe Rhodes
ACM SIGGRAPH, Los Angeles, CA, 2008
mHashup is a novel visual interface to large music collections, such as today’s million-song download services, for discovering musical relationships among tracks. Users engage in direct on-screen query and retrieval of music fragments in an instantaneous feedback flow performed by a locality sensitive hash table [...]
