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Sinan Sonlu, Uğur Güdükbay, and Funda Durupinar. A Conversational Agent Framework with Multi-Modal Personality Expression. ACM Transactions on Graphics, 40(1):Article no. 7, 16 pages, Association for Computing Machinery, New York, NY, USA, January 2021. Work presented at ACM SIGGRAPH 2021, The Premier Conference & Exhibition in Computer Graphics & Interactive Techniques, Virtual Event, 9-13 August 2021.
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Consistently exhibited personalities are crucial elements of realistic, engaging, and behavior-rich conversational virtual agents. Both nonverbal and verbal cues help convey these agentsâ unseen psychological states, contributing to our effective communication with them. We introduce a comprehensive framework to design conversational agents that express personality through non-verbal behaviors like body movement and facial expressions, as well as verbal behaviors like dialogue selection and voice transformation. We use the OCEAN personality model, which defines personality as a combination of five orthogonal factors of openness, conscientiousness, extraversion, agreeableness, and neuroticism. The framework combines existing personality expression methods with novel ones such as new algorithms to convey Laban Shape and Effort qualities. We perform Amazon Mechanical Turk studies to analyze how different communication modalities influence our perception of virtual agent personalities and compare their individual and combined effects on each personality dimension. The results indicate that our personality-based modifications are perceived as natural, and each additional modality improves perception accuracy, with the best performance achieved when all the modalities are present. We also report some correlations for the perception of conscientiousness with neuroticism and openness with extraversion.
@article{SonluGD21,
author = {Sonlu, Sinan and G{\"u}d{\"u}kbay, U{\^g}ur and Durupinar, Funda},
title = {A Conversational Agent Framework with Multi-Modal Personality Expression},
year = {2021},
month = {January},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
volume = {40},
number = {1},
pages = {Article no. 7, 16 pages},
issn = {0730-0301},
url = {https://doi.org/10.1145/3439795},
doi = {10.1145/3439795},
abstract = {Consistently exhibited personalities are crucial elements of realistic, engaging, and
behavior-rich conversational virtual agents. Both nonverbal and verbal cues help convey
these agentsâ unseen psychological states, contributing to our effective communication
with them. We introduce a comprehensive framework to design conversational agents that
express personality through non-verbal behaviors like body movement and facial expressions,
as well as verbal behaviors like dialogue selection and voice transformation. We use the
OCEAN personality model, which defines personality as a combination of five orthogonal
factors of openness, conscientiousness, extraversion, agreeableness, and neuroticism.
The framework combines existing personality expression methods with novel ones such as
new algorithms to convey Laban Shape and Effort qualities. We perform Amazon Mechanical Turk
studies to analyze how different communication modalities influence our perception of
virtual agent personalities and compare their individual and combined effects on each
personality dimension. The results indicate that our personality-based modifications are
perceived as natural, and each additional modality improves perception accuracy, with
the best performance achieved when all the modalities are present. We also report
some correlations for the perception of conscientiousness with neuroticism and
openness with extraversion.},
journal = {ACM Transactions on Graphics},
month = jan,
articleno = {7},
numpages = {16},
bib2html_dl_pdf = "https://dl.acm.org/doi/pdf/10.1145/3439795",
note = {Work presented at ACM SIGGRAPH 2021, The Premier Conference & Exhibition in Computer Graphics &
Interactive Techniques, Virtual Event, 9-13 August 2021.},
keywords = {OCEAN personality, emotion, nonverbal cues, Conversational agent, Laban movement analysis},
bib2html_pubtype = {Refereed Journal Articles},
bib2html_rescat = {Computer Graphics}
}
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