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How Much do Robots Understand Rudeness? Challenges in Human-Robot Interaction

Orme, Michael; Yu, Yanchao; Tan, Zhiyuan



This paper concerns the pressing need to understand and manage inappropriate language within the evolving human-robot interaction (HRI) landscape. As intelligent systems and robots transition from controlled laboratory settings to everyday households, the demand for polite and culturally sensitive conversational abilities becomes paramount, especially for younger individuals. This study explores data cleaning methods, focusing on rudeness and contextual similarity, to identify and mitigate inappropriate language in real-time interactions. State-of-the-art natural language models are also evaluated for their proficiency in discerning rudeness. This multifaceted investigation highlights the challenges of handling inappropriate language, including its tendency to hide within idiomatic expressions and its context-dependent nature. This study will further contribute to the future development of AI systems capable of engaging in intelligent conversations and upholding the values of courtesy and respect across diverse cultural and generational boundaries.

Presentation Conference Type Conference Paper (Published)
Conference Name The 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)
Start Date May 20, 2024
End Date May 25, 2024
Acceptance Date Feb 20, 2024
Deposit Date Mar 26, 2024
Publisher European Language Resources Association (ELRA)
Keywords Natural Language Processing; Human-Robot Interaction; Inappropriate Language
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