Friday, June 13, 2014, 01:00pm
Professor, CS Dept, Carnegie Mellon University
"Automating Music Listening and Understanding"
Abstract: New capabilities arise when we combine perception with computation: from Siri to face recognition, applications abound. Musicians have a long and close relationship with technology, so it should be no surprise that Music Understanding -- the automatic recognition of pattern and structure in music -- is not only an active research area but is delivering interesting applications for music education, music production, and music performance. Music understanding problems include (1) matching and searching symbolic and audio music sequences, (2) parsing music to discover musical objects such as sections, notes, and beats, and (3) the interpretation and generation of expressive music performance. I will demonstrate through examples some music understanding success stories, including commercial products and artistic ventures.
Bio: Prof. Roger B. Dannenberg is Professor in the Schools of Computer Science, Art, and Music at Carnegie Mellon University. His pioneering work in computer accompaniment led to three patents and the SmartMusic system now used by over one hundred thousand music students. He also played a central role in the development of the Piano Tutor and Rock Prodigy, both interactive, multimedia music education systems, and Audacity, the audio editor. Dannenberg is also known for introducing functional programming concepts to describe real-time behavior, an approach that forms the foundation for Nyquist, a widely used sound synthesis language. As a composer, Dannenberg's works have been performed by the Pittsburgh New Music Ensemble, the Pittsburgh Symphony, and at many festivals. As a trumpet player, he has collaborated with musicians including Anthony Braxton, Eric Kloss, and Roger Humphries, and performed in concert halls ranging from the historic Apollo Theater in Harlem to the Espace de Projection at IRCAM.
Hosted by: EECS Prof. Bryan Pardo as part of the CS + Music Speaker Series