Supporting page for Tristan Jehan's PhD thesis:
Creating Music by Listening


 

Online dissertation (HTML)

Downloadable dissertation (PDF)

Defense slides June 17, 2005 (with sounds)

Defense video (requires real-video)

A piece example (2 min MP3)

Several intermediary sound examples

Implementation in Skeleton

Screenshot of Skeleton

 


 

Creating Music by Listening
by Tristan Jehan

Abstract

Machines have the power and potential to make expressive music on their own. This thesis aims to computationally model the process of creating music using experience from listening to examples. Our unbiased signal-based solution models the life cycle of listening, composing, and performing, turning the machine into an active musician, instead of simply an instrument. We accomplish this through an analysis-synthesis technique by combined perceptual and structural modeling of the musical surface, which leads to a minimal data representation.

We introduce a music cognition framework that results from the interaction of psychoacoustically grounded causal listening, a time-lag embedded feature representation, and perceptual similarity clustering. Our bottom-up analysis intends to be generic and uniform by recursively revealing metrical hierarchies and structures of pitch, rhythm, and timbre. Training is suggested for top-down unbiased supervision, and is demonstrated with the prediction of downbeat. This musical intelligence enables a range of original manipulations including song alignment, music restoration, cross-synthesis or song morphing, and ultimately the synthesis of original pieces.

 


 

Thesis Committee

Thesis supervisor......................................................................
Tod Machover
Professor of Music and Media
MIT Program in Media Arts and Sciences

Thesis reader.............................................................................
Peter Cariani
Research Assistant Professor of Physiology
Tufts Medical School

Thesis reader.............................................................................
François Pachet
Senior Researcher
Sony Computer Science Laboratory

Thesis reader.............................................................................
Julius O. Smith III
Associate Professor of Music and (by courtesy) Electrical Engineering
CCRMA, Stanford University

Thesis reader.............................................................................
Barry Vercoe
Professor of Media Arts and Sciences
MIT Program in Media Arts and Sciences