arrow
Return

Fluent Human-Robot Dialogues About Grounded Objects in Home Environments

delete2014-07-05
delete4
PRE
AI
A
Andreas Persson
S
Samer Al Moubayed *
A
Amy Loutfi
DOI:10.1007/s12559-014-9291-ydelete
deleteOriginal
deleteOriginal request for help
deleteShare
deleteSave
Abstract

Abstract

En 中文
To provide a spoken interaction between robots and human users, an internal representation of the robots sensory information must be available at a semantic level and accessible to a dialogue system in order to be used in a human-like and intuitive manner. In this paper, we integrate the fields of perceptual anchoring (which creates and maintains the symbol-percept correspondence of objects) in robotics with multimodal dialogues in order to achieve a fluent interaction between humans and robots when talking about objects. These everyday objects are located in a so-called symbiotic system where humans, robots, and sensors are co-operating in a home environment. To orchestrate the dialogue system, the IrisTK dialogue platform is used. The IrisTK system is based on modelling the interaction of events, between different modules, e.g. speech recognizer, face tracker, etc. This system is running on a mobile robot device, which is part of a distributed sensor network. A perceptual anchoring framework, recognizes objects placed in the home and maintains a consistent identity of the objects consisting of their symbolic and perceptual data. Particular effort is placed on creating flexible dialogues where requests to objects can be made in a variety of ways. Experimental validation consists of evaluating the system when many objects are possible candidates for satisfying these requests.
Keywords:
Human-robot interaction
Perceptual anchoring
Symbol grounding
Spoken dialogue systems
Social robotics
AI Summary

AI Summary

Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.

Journal

Cognitive Computation cover
Cognitive Computation
IF:
4.3
Papers:
1.6K
Citations:
3.6K

Organization

R
Royal Institute of Technology
Scholars:
1.8W
Papers: 1.8W
Citations: 25
O
Orebro University
Scholars:
5.0K
Papers: 4.7K
Citations: 51