TY - JOUR
T1 - Introducing the NEMO-Lowlands iconic gesture dataset, collected through a gameful human–robot interaction
AU - Wit, Jan de
AU - Krahmer, Emiel
AU - Vogt, Paul
N1 - Funding Information:
This project has received funding from the European Union’s Horizon 2020 research and innovation programme under the Grant Agreement No. 688014.
Publisher Copyright:
© 2020, The Author(s).
PY - 2021
Y1 - 2021
N2 - This paper describes a novel dataset of iconic gestures, together with a publicly available robot-based elicitation method to record these gestures, which consists of playing a game of charades with a humanoid robot. The game was deployed at a science museum (NEMO) and a large popular music festival (Lowlands) in the Netherlands. This resulted in recordings of 428 participants, both adults and children, performing 3715 silent iconic gestures for 35 different objects in a naturalistic setting. Our dataset adds to existing collections of iconic gesture recordings in two important ways. First, participants were free to choose how they represented the broad concepts using gestures, and they were asked to perform a second attempt if the robot did not recognize their gesture the first time. This provides insight into potential repair strategies that might be used. Second, by making the interactive game available we enable other researchers to collect additional recordings, for different concepts, and in diverse cultures or contexts. This can be done in a consistent manner because a robot is used as a confederate in the elicitation procedure, which ensures that every data collection session plays out in the same way. The current dataset can be used for research into human gesturing behavior, and as input for the gesture recognition and production capabilities of robots and virtual agents.
AB - This paper describes a novel dataset of iconic gestures, together with a publicly available robot-based elicitation method to record these gestures, which consists of playing a game of charades with a humanoid robot. The game was deployed at a science museum (NEMO) and a large popular music festival (Lowlands) in the Netherlands. This resulted in recordings of 428 participants, both adults and children, performing 3715 silent iconic gestures for 35 different objects in a naturalistic setting. Our dataset adds to existing collections of iconic gesture recordings in two important ways. First, participants were free to choose how they represented the broad concepts using gestures, and they were asked to perform a second attempt if the robot did not recognize their gesture the first time. This provides insight into potential repair strategies that might be used. Second, by making the interactive game available we enable other researchers to collect additional recordings, for different concepts, and in diverse cultures or contexts. This can be done in a consistent manner because a robot is used as a confederate in the elicitation procedure, which ensures that every data collection session plays out in the same way. The current dataset can be used for research into human gesturing behavior, and as input for the gesture recognition and production capabilities of robots and virtual agents.
KW - Gesture dataset
KW - Human–robot interaction
KW - Semi-structured elicitation
UR - https://osf.io/r59hj/
U2 - 10.3758/s13428-020-01487-0
DO - 10.3758/s13428-020-01487-0
M3 - Article
SN - 1554-351X
VL - 53
SP - 1353
EP - 1370
JO - Behavior Research Methods
JF - Behavior Research Methods
IS - 3
ER -