DocumentCode
667552
Title
About this non-negative business
Author
Smaragdis, Paris
Author_Institution
Univ. of Illinois, Urbana, IL, USA
fYear
2013
fDate
20-23 Oct. 2013
Firstpage
1
Lastpage
1
Abstract
Summary form only given: The foundations of signal processing are firmly set in least squares, an approach that has served us very well for years (and still does). With the increasing presence of machine learning and sophisticated statistics in audio processing, we are slowly seeing that not everything has to be based on Gaussians anymore. One recently popular approach along these lines is that of non-negative modeling, especially in problems that involve complex audio mixtures. In this keynote I´ll talk about how these models came to be, what they can do, why they have been so successful, and I´ll ponder on what the future holds as new developments are continuously coming in.
Keywords
audio signal processing; learning (artificial intelligence); least squares approximations; audio processing; complex audio mixtures; least squares; machine learning; nonnegative modeling; signal processing; Acoustics; Business; Committees; Computer science; Conferences; Educational institutions; Signal processing;
fLanguage
English
Publisher
ieee
Conference_Titel
Applications of Signal Processing to Audio and Acoustics (WASPAA), 2013 IEEE Workshop on
Conference_Location
New Paltz, NY
ISSN
1931-1168
Type
conf
DOI
10.1109/WASPAA.2013.6701898
Filename
6701898
Link To Document