Conversational agent expressing ocean personality and emotions using laban movement analysis and nonverbal communication cues
Author(s)
Advisor
Güdükbay, UğurDate
2019-08Publisher
Bilkent University
Language
English
Type
ThesisItem Usage Stats
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Abstract
Conversational human characters are heavily used in computer animation to convey
various messages. Appearance, movement and voice of such characters in
uence
their perceived personality. Analyzing different channels of human communication,
including body language, facial expression and vocalics, it is possible
to design animation that exhibit consistent personality. This would enhance the
message and improve realism of the virtual character.
Using OCEAN personality model, we design internal agent parameters that
are mapped into movement and sound modi ers, which in turn produce the nal
animation. Laban Movement Analysis and Nonverbal Communication Cues are
used for the operations that output bone rotations and facial shape key values
at each frame. Correlations between personality and spoken text, and relations
between personality and vocal features are integrated to introduce compherensive
agent behavior.
Multiple animation modi cation algorithms and a personality based dialogue
selection method is introduced. Resulting conversational agent is tested in different
scenarios, including passport check and fastfood order. Using a speech to
text API user controls the dialog
ow. Recorded interactions are evaluated using
Amazon Mechanical Turk. Multiple statements about agent personality are rated
by the crowd. In each experiment, one personality parameter is set to an extreme
while others remain neutral, expecting an effect on perception.
Keywords
Conversational agent behaviourEmotion, computer animation
Personality
Laban movement analysis
Nonverbal communication
Computer animation