Multimodal Language Specification for Human Adaptive Mechatronics

TL;DR

This paper introduces a multimodal attribute grammar for specifying and fusing multimodal inputs in human-robot interaction, enhancing natural communication with automated systems.

Contribution

It proposes a novel multimodal attribute grammar that models semantic and temporal features, enabling effective multimodal language specification and fusion.

Findings

Successfully applied to a driver assistance system

Supports semantic and temporal modeling of multimodal inputs

Improves natural interaction with automated systems

Abstract

Designing and building automated systems with which people can interact naturally is one of the emerging objective of Mechatronics. In this perspective multimodality and adaptivity represent focal issues, enabling users to communicate more freely and naturally with automated systems. One of the basic problem of multimodal interaction is the fusion process. Current approaches to fusion are mainly two: the former implements the multimodal fusion at dialogue management level, whereas the latter at grammar level. In this paper, we propose a multimodal attribute grammar, that provides constructions both for representing input symbols from different modalities and for modeling semantic and temporal features of multimodal input symbols, enabling the specification of multimodal languages. Moreover, an application of the proposed approach in the context of a multimodal language specification to control a driver assistance system, as robots using different integrated interaction modalities, is given.