skip to main content
10.1145/2513383.2513438acmconferencesArticle/Chapter ViewAbstractPublication PagesassetsConference Proceedingsconference-collections
research-article

Do you see what I see?: designing a sensory substitution device to access non-verbal modes of communication

Published:21 October 2013Publication History

ABSTRACT

The inability to access non-verbal cues is a setback for people who are blind or visually impaired. A visual-to-auditory Sensory Substitution Device (SSD) may help improve the quality of their lives by transforming visual cues into auditory cues. In this paper, we describe the design and development of a robust and real-time SSD called iFEPS -- improved Facial Expression Perception through Sound. The implementation of the iFEPS evolved over time through a participatory design process. We conducted both subjective and objective experiments to quantify the usability of the system. Evaluation with 14 subjects (7 blind + 7 blind-folded) shows that the users were able to perceive the facial expressions in most of the time. In addition, the overall subjective usability of the system was found to be scoring 4.02 in a 5 point Likert scale.

References

  1. M. Argyle, V. Salter, H. Nicholson, M. Williams, and P. Burgess. The communication of inferior and superior attitudes by verbal and non-verbal signals*. British journal of social and clinical psychology, 9(3):222--231, 1970.Google ScholarGoogle Scholar
  2. D. Astler, H. Chau, K. Hsu, A. Hua, A. Kannan, L. Lei, M. Nathanson, E. Paryavi, M. Rosen, H. Unno, et al. Increased accessibility to nonverbal communication through facial and expression recognition technologies for blind/visually impaired subjects. In The proceedings of the 13th international ACM SIGACCESS conference on Computers and accessibility, pages 259--260. ACM, 2011. Google ScholarGoogle ScholarDigital LibraryDigital Library
  3. P. Bach-y Rita, C. Collins, F. Saunders, B. White, and L. Scadden. Vision substitution by tactile image projection. 1969.Google ScholarGoogle Scholar
  4. H. Beyer and K. Holtzblatt. Contextual design: defining customer-centered systems. Morgan Kaufmann, 1997. Google ScholarGoogle ScholarDigital LibraryDigital Library
  5. P. Ekman and W. Friesen. Facial action coding system. Consulting Psychologists Press, Stanford University, Palo Alto, 1977.Google ScholarGoogle Scholar
  6. N. A. Giudice, H. P. Palani, E. Brenner, and K. M. Kramer. Learning non-visual graphical information using a touch-based vibro-audio interface. In Proceedings of the 14th international ACM SIGACCESS conference on Computers and accessibility, ASSETS '12, pages 103--110, 2012. Google ScholarGoogle ScholarDigital LibraryDigital Library
  7. L. H. Goldish and H. E. Taylor. The optacon: A valuable device for blind persons. New Outlook for the Blind, 68(2):49--56, 1974.Google ScholarGoogle Scholar
  8. S. K. e. a. Kane. Freedom to roam: a study of mobile device adoption and accessibility for people with visual and motor disabilities. In ACM SIGACCESS conference on Computers and accessibility, pages 115--122. ACM, 2009. Google ScholarGoogle ScholarDigital LibraryDigital Library
  9. J. Loomis, R. Klatzky, and N. Giudice. Sensory substitution of vision: importance of perceptual and cognitive processing. Assistive technology for blindness and low vision. CRC Press, Boca Raton, pages 161--193, 2012.Google ScholarGoogle Scholar
  10. P. Lucey, J. Cohn, T. Kanade, J. Saragih, Z. Ambadar, and I. Matthews. The extended cohn-kanade dataset (ck+): A complete dataset for action unit and emotion-specified expression. In CVPR Workshops (CVPRW), 2010, pages 94--101. IEEE, 2010.Google ScholarGoogle ScholarCross RefCross Ref
  11. P. Meijer. An experimental system for auditory image representations. Biomedical Engineering, IEEE Transactions on, 39(2):112--121, 1992.Google ScholarGoogle Scholar
  12. M. Olivetti Belardinelli, S. Federici, F. Delogu, and M. Palmiero. Sonification of spatial information: audio-tactile exploration strategies by normal and blind subjects. Universal Access in Human-Computer Interaction. Intelligent and Ubiquitous Interaction Environments, pages 557--563, 2009. Google ScholarGoogle ScholarDigital LibraryDigital Library
  13. G. Radvansky. Human memory. Recherche, 67:02, 2005.Google ScholarGoogle Scholar
  14. A. Rahman, M. Tanveer, and M. Yeasin. A spatio-temporal probabilistic framework for dividing and predicting facial action units. In ACII-Volume Part II, pages 598--607. Springer-Verlag, 2011. Google ScholarGoogle ScholarDigital LibraryDigital Library
  15. B. S. Reddy and B. Chatterji. An fft-based technique for translation, rotation, and scale-invariant image registration. Image Processing, IEEE Transactions on, 5(8):1266--1271, 1996. Google ScholarGoogle ScholarDigital LibraryDigital Library
  16. S. Réhman and L. Liu. ifeeling: Vibrotactile rendering of human emotions on mobile phones. Mobile Multimedia Processing, pages 1--20, 2010.Google ScholarGoogle ScholarCross RefCross Ref
  17. J. Saragih, S. Lucey, and J. Cohn. Deformable model fitting by regularized landmark mean-shift. International Journal of Computer Vision, 91(2):200--215, 2011. Google ScholarGoogle ScholarDigital LibraryDigital Library
  18. M. I. Tanveer, A. I. Anam, A. M. Rahman, S. Ghosh, and M. Yeasin. Feps: a sensory substitution system for the blind to perceive facial expressions. In 14th ACM SIGACCESS conference on Computers and accessibility, ASSETS '12, pages 207--208, 2012. Google ScholarGoogle ScholarDigital LibraryDigital Library

Index Terms

  1. Do you see what I see?: designing a sensory substitution device to access non-verbal modes of communication

        Recommendations

        Comments

        Login options

        Check if you have access through your login credentials or your institution to get full access on this article.

        Sign in
        • Published in

          cover image ACM Conferences
          ASSETS '13: Proceedings of the 15th International ACM SIGACCESS Conference on Computers and Accessibility
          October 2013
          343 pages
          ISBN:9781450324052
          DOI:10.1145/2513383

          Copyright © 2013 ACM

          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 the author(s) 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].

          Publisher

          Association for Computing Machinery

          New York, NY, United States

          Publication History

          • Published: 21 October 2013

          Permissions

          Request permissions about this article.

          Request Permissions

          Check for updates

          Qualifiers

          • research-article

          Acceptance Rates

          ASSETS '13 Paper Acceptance Rate28of98submissions,29%Overall Acceptance Rate436of1,556submissions,28%

        PDF Format

        View or Download as a PDF file.

        PDF

        eReader

        View online with eReader.

        eReader