2026-09-19T16:21:17Zhttps://dspace.mit.edu/server/oai/requestoai:dspace.mit.edu:1721.1/283832022-01-13T07:54:29Zcom_1721.1_7582com_1721.1_7581col_1721.1_131023
Bruce Blumberg.
Cochran, Jennie E. (Jennie Eleanor), 1981-
Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science.
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
2005-09-26T20:09:24Z
2005-09-26T20:09:24Z
2004
2004
http://hdl.handle.net/1721.1/28383
56960644
Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2004.
Includes bibliographical references (leaf 56).
The ability to discern information from the tone of voice that a person uses is an important part of social interactions. Synthetic characters that can interact naturally with humans could take advantage of this information if they could discern it. I propose that a synthetic character with a vocalization affect classifier and the ability to learn associations can use the tone of voice of the person interacting with her to predict what the person is going to do. In this approach the classifier learns to distinguish tones in real time allowing the character to adapt to new tones. I describe the implementation of the system, called Minimus T.O. Mouse, and its extensions from previous affect classifying systems and previous synthetic characters.
by Jennie E. Cochran.
M.Eng.
56 leaves
3395873 bytes
3400732 bytes
application/pdf
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Massachusetts Institute of Technology
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http://dspace.mit.edu/handle/1721.1/7582
Electrical Engineering and Computer Science.
Learning Internet from tone of voice
Thesis
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