Communication error detection using facial expressions
Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2008.
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| Format: | Thesis |
| Language: | eng |
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Massachusetts Institute of Technology
2009
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| Online Access: | http://hdl.handle.net/1721.1/45881 |
| _version_ | 1826217232679567360 |
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| author | Wang, Sy Bor, 1976- |
| author2 | Trevor J. Darrell and David Demirdjian. |
| author_facet | Trevor J. Darrell and David Demirdjian. Wang, Sy Bor, 1976- |
| author_sort | Wang, Sy Bor, 1976- |
| collection | MIT |
| description | Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2008. |
| first_indexed | 2024-09-23T17:00:05Z |
| format | Thesis |
| id | mit-1721.1/45881 |
| institution | Massachusetts Institute of Technology |
| language | eng |
| last_indexed | 2024-09-23T17:00:05Z |
| publishDate | 2009 |
| publisher | Massachusetts Institute of Technology |
| record_format | dspace |
| spelling | mit-1721.1/458812019-04-10T08:52:45Z Communication error detection using facial expressions Wang, Sy Bor, 1976- Trevor J. Darrell and David Demirdjian. Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science. Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science. Electrical Engineering and Computer Science. Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2008. Includes bibliographical references (p. 129-135). Automatic detection of communication errors in conversational systems typically rely only on acoustic cues. However, perceptual studies have indicated that speakers do exhibit visual communication error cues passively during the system's conversational turn. In this thesis, we introduce novel algorithms for face and body gesture recognition and present the first automatic system for detecting communication errors using facial expressions during the system's turn. This is useful as it detects communication problems before the user speaks a reply. To detect communication problems accurately and efficiently we develop novel extensions to hidden-state discriminative methods. We also present results that show when human subjects become aware that the conversational system is capable of receiving visual input, they become more communicative visually yet naturally. by Sy Bor Wang. Ph.D. 2009-06-30T16:31:28Z 2009-06-30T16:31:28Z 2008 2008 Thesis http://hdl.handle.net/1721.1/45881 320238793 eng M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission. http://dspace.mit.edu/handle/1721.1/7582 135 p. application/pdf Massachusetts Institute of Technology |
| spellingShingle | Electrical Engineering and Computer Science. Wang, Sy Bor, 1976- Communication error detection using facial expressions |
| title | Communication error detection using facial expressions |
| title_full | Communication error detection using facial expressions |
| title_fullStr | Communication error detection using facial expressions |
| title_full_unstemmed | Communication error detection using facial expressions |
| title_short | Communication error detection using facial expressions |
| title_sort | communication error detection using facial expressions |
| topic | Electrical Engineering and Computer Science. |
| url | http://hdl.handle.net/1721.1/45881 |
| work_keys_str_mv | AT wangsybor1976 communicationerrordetectionusingfacialexpressions |