Conversational homes: a uniform natural language approach for collaboration among humans and devices

Braines, Dave, O'Leary, Nick, Thomas, Anna, Harborne, Daniel, Preece, Alun David ORCID: https://orcid.org/0000-0003-0349-9057 and Webberley, William M. 2017. Conversational homes: a uniform natural language approach for collaboration among humans and devices. International Journal on Advances in Intelligent Systems 10 (3/4) , pp. 223-237.

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Abstract

As devices proliferate, the ability for us to interact with them in an intuitive and meaningful way becomes increasingly challenging. In this paper we take the typical home as an experimental environment to investigate the challenges and potential solutions arising from ever-increasing device proliferation and complexity. We describe and evaluate a potential solution based on conversational interactions between “things” in the environment where those things can be either machine devices or human users. Our key innovation is the use of a Controlled Natural Language (CNL) technology as the underpinning information representation language for both machine and human agents, enabling humans and machines to trivially “read” the information being exchanged. The core CNL is augmented with a conversational protocol enabling different speech acts to be exchanged within the system. This conversational layer enables key contextual information to be conveyed, as well as providing a mechanism for translation from the core CNL to other forms, such as device specific API (Application Programming Interface) requests, or more easily consumable human representations. Our goal is to show that a single, uniform language can support machine-machine, machine-human, human-machine and humanhuman interaction in a dynamic environment that is able to rapidly evolve to accommodate new devices and capabilities as they are encountered. We also report results from our first formal evaluation of a Conversational Homes prototype and demonstrate users with no previous experience of this environment are able to rapidly and effectively interact with simulated devices in a number of simple scenarios.

Item Type:	Article
Date Type:	Publication
Status:	Published
Schools:	Computer Science & Informatics Crime and Security Research Institute (CSURI)
Publisher:	IARIA
ISSN:	1942-2679
Date of First Compliant Deposit:	23 January 2018
Date of Acceptance:	4 November 2017
Last Modified:	17 May 2023 11:59
URI:	https://orca.cardiff.ac.uk/id/eprint/108371

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