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Enabling Full Interaction with the Android System and Applications through Speech Recognition

Published: 17 October 2017 Publication History

Abstract

Mobile devices, such as smartphones and tablets, have become almost indispensable items in people's daily lives. The interaction via touches on screen has been consolidated in these devices, being quite efficient, for the majority of the cases. However, this type of interaction can be limiting, or even make impossible the use of the device, for a person with busy hands or some kind of motor difficulty. In such cases, the possibility of using voice commands to control the device may be a more attractive solution. Although some devices already offer this kind of feature, it is restricted to some features pre-determined by the system. The main goal of this work was to develop an application that allows full interaction with the device via voice commands using the speech recognition API of the Android operating system. Recognition tests were performed with the developed application, whose results demonstrated a 95% efficiency, making possible a full interaction with any application installed in the device.

References

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Agebson R. Façanha, Maria da C. C. Araújo, Windson Viana, and Mauro C. Pequeno. 2012. Le brailleTWT: Providing Visual Accessibility to Twitter on Touchscreen Devices. In Proceedings of the 18th Brazilian Symposium on Mul- timedia and the Web (WebMedia '12). ACM, New York, NY, USA, 313--320. https://doi.org/10.1145/2382636.2382703
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Alexandre Soares Silva and Jocimara Paiva Grillo. 2016. Um framework de desenvolvimento de jogos digitais para dispositivos móveis voltados à inclusão de jogadores com deficiência visual. In XV Simpósio Brasileiro de Jogos e Entrenimento Digital -- SBGames. SBC, 202--205.
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Artur Henrique Kronbauer and Vinicius Costa. 2015. A New Approach to the Interpretation of Voice Commands. In Proceedings of the 21st Brazilian Symposium on Multimedia and the Web (WebMedia '15). ACM, New York, NY, USA, 217--224. https://doi.org/10.1145/2820426.2820431
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Wu Chou and Biing-Hwang Juang. 2003.Pattern recognition in speech and language processing. CRC Press.
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Mike Schuster. 2010. Speech recognition for mobile devices at Google. In Pacific Rim International Conference on Artificial Intelligence. Springer, 8--10.
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Xin Lei, Andrew W Senior, Alexander Gruenstein and Jeffrey Sorensen. 2013. Accurate and compact large vocabulary speech recognition on mobile devices. In Interspeech.
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Raj Jain. 1991.The Art of Computer Systems Performance Analysis: Techniques for Experimental Design, Measurement, Simulation and Modeling. John Wiley & Sons.

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  1. Enabling Full Interaction with the Android System and Applications through Speech Recognition

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    cover image ACM Other conferences
    WebMedia '17: Proceedings of the 23rd Brazillian Symposium on Multimedia and the Web
    October 2017
    522 pages
    ISBN:9781450350969
    DOI:10.1145/3126858
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

    Sponsors

    • SBC: Brazilian Computer Society
    • CNPq: Conselho Nacional de Desenvolvimento Cientifico e Tecn
    • CGIBR: Comite Gestor da Internet no Brazil
    • CAPES: Brazilian Higher Education Funding Council

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    Association for Computing Machinery

    New York, NY, United States

    Publication History

    Published: 17 October 2017

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    Author Tags

    1. accessibility
    2. android
    3. speech recognition.

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    Webmedia '17
    Sponsor:
    • SBC
    • CNPq
    • CGIBR
    • CAPES
    Webmedia '17: Brazilian Symposium on Multimedia and the Web
    October 17 - 20, 2017
    RS, Gramado, Brazil

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    WebMedia '17 Paper Acceptance Rate 38 of 138 submissions, 28%;
    Overall Acceptance Rate 270 of 873 submissions, 31%

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