Smooth turn-taking is an important aspect of natural conversation that allows interlocutors to maintain adequate mutual comprehensibility. In human communication, the timing between utterances is normatively constrained, and deviations convey socially relevant paralinguistic information. However, for spoken dialogue systems, smooth turn-taking continues to be a challenge. This motivates the need for spoken dialogue systems to employ a robust model of turn-taking to ensure that messages are exchanged smoothly and without transmitting unintended paralinguistic information. In this paper, we examine dialogue data from natural human interaction to develop an evidence-based model for turn-timing in spoken dialogue systems. First, we use timing between turns to develop two models of turn-taking: a speaker-agnostic model and a speaker-sensitive model. From the latter model, we derive the propensity of listeners to take the next turn given TRP duration. Finally, we outline how this measure may be incorporated into a spoken dialogue system to improve the naturalness of conversation.

Turn taking in conversation is a complex process. We still don’t know how listeners are able to anticipate the end of a speaker’s turn. Previous work focuses on prosodic, semantic, and non-verbal cues that a turn is coming to an end. In this paper, we look at simple measures of duration — time, word count, and syllable count — to see if we can exploit the duration of turns as a cue. We find strong evidence that these metrics are useless.