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LREC-COLING 2024main

Analysis of Sensation-transfer Dialogues in Motorsports

Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)

DOI:10.63317/5o7y3md38zfh

Abstract

Clarifying the effects of subjective ideas on group performance is essential for future dialogue systems to improve mutual understanding among humans and group creativity. However, there has been little focus on dialogue research on quantitatively analyzing the effects of the quality and quantity of subjective information contained in dialogues on group performance. We hypothesize that the more subjective information interlocutors exchange, the better the group performance in collaborative work. We collected dialogues between drivers and engineers in motorsports when deciding how the car should be tuned as a suitable case to verify this hypothesis. Our analysis suggests that the greater the amount of subjective information (which we defined as “sensation”) in the driver’s utterances, the greater the race performance and driver satisfaction with the car’s tuning. The results indicate that it is essential for the development of dialogue research to create a corpus of situations that require high performance through collaboration among experts with different backgrounds but who have mastered their respective fields.

Details

Paper ID
lrec2024-main-0079
Pages
pp. 876-886
BibKey
isaka-etal-2024-analysis
Editor
N/A
Publisher
European Language Resources Association (ELRA) and ICCL
ISSN
2522-2686
ISBN
979-10-95546-34-4
Conference
Joint International Conference on Computational Linguistics, Language Resources and Evaluation
Location
Turin, Italy
Date
20 May 2024 25 May 2024

Authors

  • TI

    Takeru Isaka

  • AO

    Atsushi Otsuka

  • IT

    Iwaki Toshima

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