Abstract
This paper reports empirical results showing the difference between human-human and human-artifact interactions, and proposes human interaction strategies that are useful in designing human-agents based on human behavioral models. Our empirical study uses a PC operation task as a corpus collection experiment, and reveals human-artifact interaction strategies by analyzing how verbal/nonverbal behaviors are allocated in human-human and human-artifact interactions. First, as basic characteristics in human-human and human-artifact conversations, we found that in human-artifact interactions, the number of utterances and frequency of acknowledgements and other responses are smaller than those in human-human conversations. Then, we propose human-human verbal/nonverbal behavior allocation rules, and examine how these rules are violated in human-artifact interactions, suggesting that these violations are complementary behaviors by the listener that displays understanding of the utterance to the speaker without using a verbal response.
