Expressing Coherent Personality with Incremental Acquisition of Multimodal Behaviors

As social robots increasingly enter people's lives, coherence of personality is an important challenge for longterm human-robot interactions. We extend an architecture that acquires dialog through crowdsourcing to author both verbal and non-verbal indicators of personality. We demonstrate the efficacy of the approach through a four-day study in which teams of participants interacted with a social robot expressing one of two personalities as the host of a competitive game. Results indicate that the system is able to elicit personality-driven language behaviors from the crowd in an incremental and ongoing way and produce a coherent expression of that personality during face-to-face interactions over time.