Lab Home | Phone | Search
Center for Nonlinear Studies  Center for Nonlinear Studies
 Colloquia Archive 
 Postdoc Seminars Archive 
 Quantum Lunch 
 CMS Colloquia 
 Q-Mat Seminars 
 Q-Mat Seminars Archive 
 Kac Lectures 
 Dist. Quant. Lecture 
 Ulam Scholar 
 Summer Research 
 Past Visitors 
 History of CNLS 
 Maps, Directions 
 CNLS Office 
Wednesday, October 29, 2008
3:00 PM - 4:00 PM
CNLS Conference Room (TA-3, Bldg 1690)


IS&T Center Seminar Series: Acoustic Scene Analysis, Complex Modulations and a New Form of Filtering

Les Atlas
Electrical Engineering Department, Washington University

Be it in a restaurant or other reverberant and noisy environment, normal hearing listeners segregate multiple sources, usually strongly overlapping in frequency, well beyond the capabilities expected by current beamforming approaches. What is it that we can learn from this common observation? As is now commonly accepted, the differing dynamical modulation patterns of the sources are key to these powers of separation. But until recently, the theoretical underpinnings for the notion of dynamical modulation patterns have been lacking. We have taken a previously loosely defined concept, called “modulation frequency analysis,” and developed a theory which allows for distortion-free separation (filtering) of multiple sound sources with differing dynamics. A key result is that previous assumptions of non-negative and real modulation are not sufficient and, instead, coherent separation approaches are needed to separate different modulation patterns. These results may have an impact in separation and representation of multiple simultaneous sound streams for speech, audio, hearing loss treatment, and underwater acoustic applications. This research also suggests exciting new and potentially important open theoretical questions for general nonstationary signal representations,extending beyond acoustic applications and potentially impating other areas of engineering and physics." I added this to the end og the announcement below.

Host: John Hogden, Information Sciences (CCS-3)