Multimodal Language Specification for Human Adaptive Mechatronics
This addresses the challenge of natural communication with automated systems for users in mechatronics, though it appears incremental as it builds on existing fusion approaches.
The paper tackles the problem of multimodal fusion in human-machine interaction by proposing a multimodal attribute grammar that models semantic and temporal features of input symbols, enabling specification of multimodal languages, with an application demonstrated in controlling a driver assistance system.
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.