A Multiparty Multimodal Architecture for Realtime Turntaking

Many dialogue systems have been built over the years that address some subset of the many complex factors that shape the behavior of participants in a face-to-face conversation. The Ymir Turntaking Model (YTTM) is a broad computational model of conversational skills that has been in development for over a decade, continuously growing in the number of factors it addresses. In past work we have shown how it addresses realtime dialogue, communicative gesture, perception of turntaking signals (e.g. prosody, gaze, manual gesture), dialogue planning, learning of multimodal turn signals, and dynamic adaptation to human speaking style. The architectural principles of the YTTM prescribe smaller architectural granularity than most other models, and its principles allow non-destructive additive expansion. In this paper we show how the YTTM accommodates

multi-party dialogue

. The extension has been implemented in a virtual environment; we present data for up to 12 simulated participants participating in realtime cooperative dialogue. The system includes dynamically adjustable parameters for impatience, willingness to give turn and eagerness to speak.