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Learning Non-verbal Behavior for a Social Robot from YouTube Videos
KTH, School of Electrical Engineering and Computer Science (EECS), Speech, Music and Hearing, TMH.ORCID iD: 0000-0003-3687-6189
KTH, School of Electrical Engineering and Computer Science (EECS), Robotics, Perception and Learning, RPL.ORCID iD: 0000-0001-9838-8848
KTH, School of Electrical Engineering and Computer Science (EECS), Speech, Music and Hearing, TMH.
KTH, Superseded Departments (pre-2005), Speech, Music and Hearing.ORCID iD: 0000-0003-1399-6604
2019 (English)Conference paper, Poster (with or without abstract) (Refereed)
Abstract [en]

Non-verbal behavior is crucial for positive perception of humanoid robots. If modeled well it can improve the interaction and leave the user with a positive experience, on the other hand, if it is modelled poorly it may impede the interaction and become a source of distraction. Most of the existing work on modeling non-verbal behavior show limited variability due to the fact that the models employed are deterministic and the generated motion can be perceived as repetitive and predictable. In this paper, we present a novel method for generation of a limited set of facial expressions and head movements, based on a probabilistic generative deep learning architecture called Glow. We have implemented a workflow which takes videos directly from YouTube, extracts relevant features, and trains a model that generates gestures that can be realized in a robot without any post processing. A user study was conducted and illustrated the importance of having any kind of non-verbal behavior while most differences between the ground truth, the proposed method, and a random control were not significant (however, the differences that were significant were in favor of the proposed method).

Place, publisher, year, edition, pages
2019.
Keywords [en]
Facial expressions, non-verbal behavior, generative models, neural network, head movement, social robotics
National Category
Computer Systems
Research subject
Computer Science
Identifiers
URN: urn:nbn:se:kth:diva-261242OAI: oai:DiVA.org:kth-261242DiVA, id: diva2:1357431
Conference
ICDL-EpiRob Workshop on Naturalistic Non-Verbal and Affective Human-Robot Interactions, Oslo, Norway, August 19, 2019
Funder
Swedish Foundation for Strategic Research , RIT15-0107
Note

QC 20191007

Available from: 2019-10-03 Created: 2019-10-03 Last updated: 2019-10-07Bibliographically approved

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Jonell, PatrikKucherenko, TarasEkstedt, ErikBeskow, Jonas
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Speech, Music and Hearing, TMHRobotics, Perception and Learning, RPLSpeech, Music and Hearing
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