2006 Presentations (Communicative Events)

Using Learned Source Models to Organize Sound Mixtures

Ellis, Daniel P. W.

Analyzing sound mixtures into individual waveforms proves very difficult, except in constrained circumstances such as a small number of spatially-compact sources. However, a higher-level task of recognizing simultaneous phrases from a constrained grammar is unexpectedly successful. I will argue that strong expectations, in the form of prior models of source signals, are the key to seemingly impossible source separation problems. The challenge, then, for both computational systems and models of human audition, is how to construct, represent, and deploy these models.