Semantic Communication with Conceptual Spaces

TL;DR

This paper proposes a new semantic communication framework using conceptual spaces and functional compression, achieving significant data rate reduction in image semantics transmission.

Contribution

It introduces a novel semantic communication model based on conceptual spaces and demonstrates its effectiveness through simulations.

Findings

Achieved 99.79% reduction in communication rate for image semantics

Proposed a model that transitions communication from technical to semantic level

Demonstrated the potential of conceptual spaces in semantic communication

Abstract

Despite the fact that Shannon and Weaver's Mathematical Theory of Communication was published over 70 years ago, all communication systems continue to operate at the first of three levels defined in this theory: the technical level. In this letter, we argue that a transition to the semantic level embodies a natural, important step in the evolution of communication technologies. Furthermore, we propose a novel approach to engineering semantic communication using conceptual spaces and functional compression. We introduce a model of semantic communication utilizing this approach, and simulate communication of image semantics demonstrating a 99.79% reduction in rate.