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Landmark mining on a smartwatch using speech recognition

Published: 30 November 2015 Publication History

Abstract

The smartwatch is a representative of the wearables, mini-computers worn on the body, which often only require casual interaction. In this project the advantages of smartwatches should be used to add landmarks to a database as performantly as possible and provide them for further usage. The mobile terminal should therefore be operated with voice input in a clearly structured speech dialogue to make the interaction as simple and intuitive as possible. Additionally a smartphone paired with the smartwatch distributes the user's GPS-data which help to gather data for landmarks in URWalking, a research project for pedestrian navigation at the University of Regensburg. The special problem is on the one hand to find solutions for hardware-related limitations such as a very small display size. On the other hand a way for the translation of plain-language input to technically evaluable data has to be found. In a final evaluation the system should be tested under real-life circumstances.

References

[1]
Pengfei Liu, Yanhua Chen, Wulei Tang, and Qiang Yue. 2012. Mobile WEKA as Data Mining Tool on Android. In Advances in Electrical Engineering and Automation, Anne Xie and Xiong Huang (Eds.). Springer, Berlin/Heidelberg, 75--80.
[2]
Reza Rawassizadeh, Blaine A. Price, and Marian Petre. 2015. Wearables: Has the Age of Smartwatches Finally Arrived? Communication of the ACM 58, 1 (January 2015), 45--47. httpp://dx.doi.org/10.1145/2629633
[3]
Katie A. Siek, Yvonne Rogers, and Kay H. Connelly. 2005. Fat Finger Worries: How Older and Younger Users Physically Interact with PDAs. In Proceedings of the IFIP International Conference on Human Computer Interaction (INTERACT '05). 267--280. httpp://dx.doi.org/10.1007/11555261_24
[4]
Chris Veness. Calculate Distance, Bearing and More Between Latitude/Longitude Points. 2015. Retrieved August 2, 2015 from http: //www.movable-type.co.uk/scripts/latlong.html
[5]
Universität Regensburg. Indoor and Outdoor Intuitive Guidance. 2013. Retrieved July 24, 2015 from http://www.uni-regensburg.de/sprache-literatur-kultur/informationswissenschaft/medien/2013_flyer_cebit_final.pdf

Cited By

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  • (2019)Applying user-centred design for smartwatch-based pedestrian navigation systemJournal of Location Based Services10.1080/17489725.2019.161058213:3(213-237)Online publication date: 17-May-2019
  • (2017)Inferring Landmarks for Pedestrian Navigation from Mobile Eye-Tracking Data and Google Street ViewProceedings of the 2017 CHI Conference Extended Abstracts on Human Factors in Computing Systems10.1145/3027063.3053201(2721-2729)Online publication date: 6-May-2017

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    Published In

    cover image ACM Other conferences
    MUM '15: Proceedings of the 14th International Conference on Mobile and Ubiquitous Multimedia
    November 2015
    442 pages
    ISBN:9781450336055
    DOI:10.1145/2836041
    Permission to make digital or hard copies of part or all 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 third-party components of this work must be honored. For all other uses, contact the Owner/Author.

    Sponsors

    • FH OOE: University of Applied Sciences Upper Austria
    • Johannes Kepler Univ Linz: Johannes Kepler Universität Linz

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    Association for Computing Machinery

    New York, NY, United States

    Publication History

    Published: 30 November 2015

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    Author Tags

    1. landmark-mining
    2. mobile computing
    3. smartwatch
    4. speech recognition
    5. user assistance
    6. wearables

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    MUM '15
    Sponsor:
    • FH OOE
    • Johannes Kepler Univ Linz

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    MUM '15 Paper Acceptance Rate 33 of 89 submissions, 37%;
    Overall Acceptance Rate 190 of 465 submissions, 41%

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    Cited By

    View all
    • (2019)Applying user-centred design for smartwatch-based pedestrian navigation systemJournal of Location Based Services10.1080/17489725.2019.161058213:3(213-237)Online publication date: 17-May-2019
    • (2017)Inferring Landmarks for Pedestrian Navigation from Mobile Eye-Tracking Data and Google Street ViewProceedings of the 2017 CHI Conference Extended Abstracts on Human Factors in Computing Systems10.1145/3027063.3053201(2721-2729)Online publication date: 6-May-2017

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