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Recognition and Characterization of Unstructured Environmental Sounds

Monday, February 13, 2012 -
4:00pm to 4:50pm
Weniger 149

Speaker Information

Selina Chu
Postdoctoral Associate
School of EECS
Oregon State University


Recognizing environmental sounds is a basic audio signal processing problem. Consider, for example, applications in robotic navigation, assistive robotics, and other mobile device-based services, where context aware processing is often desired. Human beings utilize both vision and hearing to navigate and respond to their surroundings, a capability still quite limited in machine processing. The first step toward achieving multi-modality is the ability to process unstructured audio and recognize audio scenes (or environments). The goal of this work is on the characterization of unstructured environmental sounds for understanding and predicting the context surrounding of an agent or device. This work investigates issues in characterizing unstructured environmental sounds and the development of appropriate feature extraction algorithm and learning techniques for modeling the variations of the acoustic environment.

Speaker Bio

Selina Chu is a postdoctoral researcher in the School of EECS at Oregon State University and a NSF/CRA Computing Innovation Fellow. She received her PhD from the Computer Science department at University of Southern California in 2011. She was a member of the Speech Analysis and Interpretation Lab and also the Multimedia Communications Lab, where she worked with Prof. Shri Narayanan and Prof. C.-C. Jay Kuo. She holds a M.S. in Information and Computer Science from University of California-Irvine and B.S. in Electrical Engineering from California State Polytechnic University. Her general research interests include machine learning, data mining, audio signal processing, and pattern recognition.