You cannot speak and listen at the same time: a probabilistic model of turn-taking

Abstract

Turn-taking is a preverbal skill whose mastering constitutes an important precondition for many social interactions and joint actions. However, the cognitive mechanisms supporting turn-taking abilities are still poorly understood. Here, we propose a computational analysis of turn-taking in terms of two general mechanisms supporting joint actions: action prediction (e.g., recognizing the interlocutor's message and predicting the end of turn) and signaling (e.g., modifying one's own speech to make it more predictable and discriminable). We test the hypothesis that in a simulated conversational scenario dyads using these two mechanisms can recognize the utterances of their co-actors faster, which in turn permits them to give and take turns more efficiently. Furthermore, we discuss how turn-taking dynamics depend on the fact that agents cannot simultaneously use their internal models for both action (or messages) prediction and production, as these have different requirements-or, in other words, they cannot speak and listen at the same time with the same level of accuracy. Our results provide a computational-level characterization of turn-taking in terms of cognitive mechanisms of action prediction and signaling that are shared across various interaction and joint action domains.

Model-Based Approaches to Active Perception and Control

“…Given that it can simultaneously address domains of perception, action, and interoception [65,66,90], as well as of individual and social cognition [91][92][93][94][95][96][97] within a unitary theoretical framework, Active Inference has recently gained considerable prominence in computational and systems neuroscience [18], as well as in philosophy-although in the former field it is more commonly referred to as a "Free Energy Principle (FEP)" framework [18], while in the latter field it is more commonly referred to as a "Predictive Processing (PP)" [62,[98][99][100] and/or "prediction error minimization (PEM)" [99] framework (henceforth, we will use these terms in an interchangeable way). Interestingly, the PP framework includes elements of both computational theories of cognition (e.g., inferential processes and internal models) and embodied and enactive theories of cognition (e.g., the contribution of action to cognitive processing and the importance of self-organizing processes and autopoiesis [101,102]) and it has been advocated by proponents of both representational and internalist theories [99] and ecological perspectives [103]; see also [98,104].…”

Haptic communication optimises joint decisions and affords implicit confidence sharing

“…Our results have deep theoretical and technological implications. From a theoretical perspective, our findings run against the hypothesis that explicit communication is necessary to achieve optimal decisions or to communicate confidence; suggesting that classical theories of communication should be expanded to consider more fully sensorimotor exchanges 13,14,[49][50][51][52][53][54] . From a technological perspective, our results can pave the way to the development of novel negotiation and decision support tools that exploit fast sensorimotor channels to facilitate and improve group decisions.…”

The neural oscillatory markers of phonetic convergence during verbal interaction

“…In conclusion, mutual understanding might be the result of a joint process whereby alignment of situation models is facilitated when interlocutors align their behavioral output (Pickering & Garrod, ; Schoot et al, 2016). Also, the fast‐paced interactive nature of dialogs suggests that speech and language understanding and production form a shared process that is co‐constructed by participants (Donnarumma, Dindo, Iodice, & Pezzulo, ). Along these lines, an emerging trend suggests that a complete grasp of the neural and cognitive processes involved in speech‐based communication cannot be achieved without examining more realistic interactions among individuals (Hasson et al, ; Pickering & Garrod, ; Schoot et al, 2016).…”