Dialogue patterns of an arabic robot receptionist

Abstract

Hala is a bilingual (Arabic and English) culturally-sensitive robot receptionist located at Carnegie Mellon University in Qatar. We report results from Hala's deployment by comparing her English dialogue corpus to that of a similar monolingual robot (named "Tank") located at CMU's Pittsburgh campus. Specifically, we compare the average number of turns per interaction, duration of interactions, frequency of interactions with personal questions, rate of non-understandings, and rate of thanks after the robot's answer. We provide possible explanations for observed similarities and differences and highlight potential cultural implications on the interactions.