2007 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.