DeLiang Wang; Ohio State University
Monday Morning, May 17, 9:00 - 12:00, Location: Marquette
The acoustic environment is typically composed of multiple simultaneous events, and a remarkable achievement of the auditory system is its ability to disentangle the acoustic mixture and group the acoustic energy that originates from the same event or source. This process of auditory grouping and segregation is referred to as auditory scene analysis (ASA). Decades of psychoacoustic research has uncovered a number of principles responsible for ASA, which motivated an emerging field of study called computational auditory scene analysis (CASA). CASA aims at sound source separation based on ASA cues, including pitch, location, amplitude/frequency modulation, and onset/offset. Recent developments in CASA show promising results in segregating speech from a variety of intrusions, where traditional signal-processing methods have difficulty. This tutorial will review recent CASA models and systems after a summary of related psychoacoustic results. An outline of the topics to be covered is the following:
DeLiang Wang received the B.S. degree in 1983 and the M.S. degree in 1986 from Peking (Beijing) University, China, and the Ph.D. degree in 1991 from the University of Southern California, all in computer science. Since 1991, he has been with the Department of Computer and Information Science and the Center for Cognitive Science at the Ohio State University (OSU), where he is Professor. He was a visiting scientist in Harvard University Department of Psychology in 1998-1999. His main research interest is machine perception. He has published some 50 papers in leading scientific journals, and numerous conference papers and book chapters. He is a recipient of the U.S. National Science Foundation Research Initiation Award in 1992 and the Office of Naval Research Young Investigator Award in 1996. He is an IEEE Fellow.
He currently serves on the editorial boards of IEEE Transactions on Neural Networks, Neurocomputing, Neurocomputing & Applications. He has served either as organizer for or on program committee of many scientific conferences, including ICASSP, World Congress on Computational Intelligence, and International Joint Conference on Neural Networks. He serves on IEEE Signal Processing Society Machine Learning for Signal Processing Technical Committee, IEEE Neural Networks Society Neural Networks Technical Committee, and Governing Board of International Neural Network Society.
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