Detecting emotion in speech: experiments in three domains

Authors:
Jackson Liscombe
Affiliations:
Columbia University
Venue:
NAACL-DocConsortium '06 Proceedings of the 2006 Conference of the North American Chapter of the Association for Computational Linguistics on Human Language Technology: companion volume: doctoral consortium
Year:
2006

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Abstract

The goal of my proposed dissertation work is to help answer two fundamental questions: (1) How is emotion communicated in speech? and (2) Does emotion modeling improve spoken dialogue applications? In this paper I describe feature extraction and emotion classification experiments I have conducted and plan to conduct on three different domains: EPSaT, HMIHY, and ITSpoke. In addition, I plan to implement emotion modeling capabilities into ITSpoke and evaluate the effectiveness of doing so.