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 :
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