人とロボットの対話における話し方の違いがもたらす影響と要因
Consequences and Factors of Stylistic Differences in Human-Robot Dialogue
人とロボットの対話コーパスを分析し、指示の冗長さや構造の違いが誤解の発生率やユーザーの信頼・経験と相関することを明らかにした研究。
著者: Stephanie M. Lukin, Kimberly A. Pollard, Claire Bonial, Matthew Marge, Cassidy Henry, Ron Arstein, David Traum, Clare R. Voss
分類: cs.CL, cs.HC, cs.RO
原文アブストラクト
This paper identifies stylistic differences in instruction-giving observed in a corpus of human-robot dialogue. Differences in verbosity and structure (i.e., single-intent vs. multi-intent instructions) arose naturally without restrictions or prior guidance on how users should speak with the robot. Different styles were found to produce different rates of miscommunication, and correlations were found between style differences and individual user variation, trust, and interaction experience with the robot. Understanding potential consequences and factors that influence style can inform design of dialogue systems that are robust to natural variation from human users.
