Malavasi, M., Turri, E., Atria, J.J. et al. (6 more authors) (2017) An innovative speech-based user interface for smarthomes and IoT solutions to help people with speech and motor disabilities. Studies in Health Technology and Informatics, 242. pp. 306-313. ISSN 0926-9630
Abstract
A better use of the increasing functional capabilities of home automation systems and Internet of Things (IoT) devices to support the needs of users with disability, is the subject of a research project currently conducted by Area Ausili (Assistive Technology Area), a department of Polo Tecnologico Regionale Corte Roncati of the Local Health Trust of Bologna (Italy), in collaboration with AIAS Ausilioteca Assistive Technology (AT) Team. The main aim of the project is to develop experimental low cost systems for environmental control through simplified and accessible user interfaces. Many of the activities are focused on automatic speech recognition and are developed in the framework of the CloudCAST project. In this paper we report on the first technical achievements of the project and discuss future possible developments and applications within and outside CloudCAST.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Editors: |
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Copyright, Publisher and Additional Information: | © 2017 IOS Press. This is an author produced version of a paper subsequently published in Harnessing the Power of Technology to Improve Lives (Studies in Health Technology and Informatics). Uploaded in accordance with the publisher's self-archiving policy. |
Keywords: | Assistive technology (AT); Disability; Dysarthria; Internet of Things (IoT); Smart home; Speech recognition |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Computer Science (Sheffield) The University of Sheffield > Faculty of Medicine, Dentistry and Health (Sheffield) > School of Health and Related Research (Sheffield) > ScHARR - Sheffield Centre for Health and Related Research |
Funding Information: | Funder Grant number TORONTO REHABILITATION INSTITUTE - UNIVERSITY HEALTH NETWORK UNSPECIFIED |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 23 Nov 2017 11:48 |
Last Modified: | 23 Nov 2017 14:28 |
Published Version: | https://doi.org/10.3233/978-1-61499-798-6-306 |
Status: | Published |
Publisher: | IOS Press |
Series Name: | Studies in Health Technology and Informatics |
Refereed: | Yes |
Identification Number: | 10.3233/978-1-61499-798-6-306 |
Related URLs: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:121314 |