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      A Smart Nocturnal Environment Monitoring System for the Hearing Impaired


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      Proceedings of the 32nd International BCS Human Computer Interaction Conference (HCI)

      Human Computer Interaction Conference

      4 - 6 July 2018

      Hearing, Intelligent, Machine learning, Prototype



            This paper presents a novel machine learning prototype to actively assist hearing-impaired people during sleeping hours. The prototype can learn ambient sounds and intelligently decide if they are indicative of dangerous situations such as warning alarms, or if they are merely unimportant background sounds. The application is targeted towards the hearing-impaired who will have removed hearing aids or external components of cochlear implants before sleep. Any sounds of importance can then be translated into vibrations to awaken the sleeping hearing impaired user. The system is suggestive of future smart interactive machines to assist and protect those with either hearing loss or profound deafness.


            Author and article information

            July 2018
            July 2018
            : 1-3
            [0001]Ulster University

            Shore Road, N’abbey

            Co.Antrim, BT370QB
            © Finlay et al. Published by BCS Learning and Development Ltd. Proceedings of British HCI 2018. Belfast, UK.

            This work is licensed under a Creative Commons Attribution 4.0 Unported License. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/

            Proceedings of the 32nd International BCS Human Computer Interaction Conference
            Belfast, UK
            4 - 6 July 2018
            Electronic Workshops in Computing (eWiC)
            Human Computer Interaction Conference
            Product Information: 1477-9358BCS Learning & Development
            Self URI (journal page): https://ewic.bcs.org/
            Electronic Workshops in Computing


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