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Paper data
Detection of focal points in speech prosody

Valbonesi Lucia, University of Illinois at Chicago
Ansari Rashid, University of Illinois at Chicago
McNeill David, University of Chicago
Quek Francis, Wright State University
Duncan Susan, University of Chicago
McCullough Karl-Eric, University of Chicago

Page numbers in the proceedings:
Volume III pp 109-112

Multimedia Data Protection / Speech Analysis and Recognition

Paper abstract
Signal processing tools are developed to help automatically detect significant events or focal points in the speech and gesture traces of audio-visual data and investigate their temporal correlation as part of a multi-disciplinary effort to assemble the computational resources for facilitating research in gesture, speech, and gaze (GSG) interaction. One key step in this research is to determine focal points in the speech signal by analyzing its acoustic-prosodic features. This task requires processing and analysis of an immense amount of data. In order to make the task efficient and less time consuming, algorithms for speech processing are developed to perform automatic feature extraction, parametric representation, and detection of focal points that are usually painstakingly marked by hand. In this paper a method for detecting the focal points in speech prosody is presented and the results are compared to the events hand marked by experts. The method produces a high rate of successful detection.

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