Presentations (Communicative Events)

Using Sound Source Models to Organize Mixtures

Ellis, Daniel P. W.

Recovering individual source signals from sound mixtures is almost always highly underconstrained, and is made possible only when additional assumptions are made about the form of the sources, mixture process, or both. Many perceptual phenomena, including restoration and illusions, reveal how strongly human listeners can rely on prior expectations to solve perceptual challenges. The basis of our computational work is to equate these expectations with internal models of source behavior, delineating the limited subset of possible sounds that are expected to occur, and thereby providing the constraints to solve the problem. I will review some relevant perceptual phenomena, then discuss how source models, of different degrees of complexity, can be used to help to understand and separate sound mixtures, including speech mixed with nonstationary interference.


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More About This Work

Academic Units
Electrical Engineering
Published Here
July 13, 2012


Presented at the Audio Signal Processing Network in Denmark Seminar on Computational Auditory Scene Analysis, Technical University of Denmark, May 24, 2007.