Does voice anthropomorphism affect lexical alignment in speech-based human-computer dialogue?

A common observation in dialogue research is that people tend to entrain, or align, linguistically with their interlocutors. This phenomenon offers a potentially important way to shape user behavior in human-computer dialogue interactions but little is known about the mechanisms that underlie it and how they may be affected by interlocutor design. We report a Wizard of Oz study that explored how voice anthropomorphism impacts lexical alignment in speech-based human-computer dialogue. In a referential communication task, speakers showed a very strong tendency to align lexical choices with their interlocutors, whether human or computer, but this tendency was not affected by voice anthropomorphism. These results highlight the robustness of lexical alignment effect in speech based human-computer dialogues, and suggest that these effects may be impervious to at least some design cues. They also suggest that automatic priming may be an influential mechanism in explaining why we align lexically with automated dialogue partners.