HCNov 11, 2021

MaTIC: a Mathematical Theory of Inferential Communication

arXiv:2111.06288v1
Originality Synthesis-oriented
AI Analysis

This work addresses the need for a precise mathematical framework to enhance multi-modal communication in immersive technologies, though it appears incremental as it builds on existing inferential models.

The authors tackled the lack of a formal mathematical theory to compare human-virtual character communication with pragmatic inference in everyday interactions, and introduced MaTIC to formalize inferential communication assumptions and outline practical applications.

The arrival of Immersive Virtual and Augmented Reality hardware to the consumer market suggests seamless multi-modal communication between human participants and autonomous interactive characters is an achievable goal in the near future. This possibility is further reinforced by the rapid improvements in the automated analysis of speech, facial expressions and body language, as well as improvements in character animation and speech synthesis techniques. However, we do not have a formal theory that allows us to compare, on one side, interactive social scenarios among human users and autonomous virtual characters and, on the other side, pragmatic inference mechanisms as they occur in non-mediated communication. Grices' and Sperbers' model of inferential communication does explain the nature of everyday communication through cognitive mechanisms that support spontaneous inferences performed in pragmatic communication. However, such a theory is not based on a mathematical framework with a precision comparable to classical information theory. To address this gap, in this article we introduce a Mathematical Theory of Inferential Communication (MaTIC). MaTIC formalises some assumptions of inferential communication, it explores its theoretical consequences and outlines the practical steps needed to use it in different application scenarios.

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