Paris Smaragdis on striving for computational and physical efficiency in audio processing
Paris has done many interesting and creative kinds of audio processing. And now he is thinking about what algorithms make sense in the real world, where time and energy matter.
Who: Paris Smaragdis (Univ of Illinois)
What: Striving for computational and physical efficiency in audio enhancement
When: Friday April 21 at 10:30AM
Where: CCRMA Seminar Room (Top floor of the Knoll)
Why: Because cool algorithms should be cool
This was an interesting talk at HSCMA and I’m looking forward to a healthy discussion at CCRMA. Come to CCRMA on Friday and find out more.
Paris Smaragdis, University of Illinois–Urbana Champaign
Title: Striving for computational and physical efficiency in audio enhancement
As commonplace speech-enabled devices are getting smaller and lighter, we are faced with a need for simpler processing and simpler hardware. In this talk I will present some alternative ways to approach multi-channel and single-channel speech enhancement under these constraints. More specifically, I will talk about new ways to formulate beamforming that are numerically more lightweight, and operate best when using physically compact arrays, and then I will discuss single-channel approaches using a deep network which, in addition to imposing a lightweight computational load, are amenable to aggressive hardware optimizations that can result in massive power savings and reductions in hardware footprint.
Paris Smaragdis is an associate professor at the Computer Science and the Electrical and Computer Engineering departments of the University of Illinois at Urbana-Champaign, as well as a senior research scientist at Adobe Research. He completed his masters, PhD, and postdoctoral studies at MIT, performing research on computational audition. In 2006 he was selected by MIT’s Technology Review as one of the year’s top young technology innovators for his work on machine listening, in 2015 he was elevated to an IEEE Fellow for contributions in audio source separation and audio processing, and during 2016-2017 he is an IEEE Signal Processing Society Distinguished Lecturer. He has authored more than 100 papers on various aspects of audio signal processing, holds more than 40 patents worldwide, and his research has been productized by multiple companies.