skip to main content
research-article
Free Access

The practice of applying AI to benefit visually impaired people in China

Published:25 October 2021Publication History
First page image

References

  1. Li, L., Wang, C., Song, S., Yu, Z., Zhou, F., and Bu, J. A task assignment strategy for crowdsourcing-based Web accessibility evaluation system. In Proceedings of the 14th Web for All Conf. on The Future of Accessible Work. (2017).Google ScholarGoogle ScholarDigital LibraryDigital Library
  2. Liu, G., Xu, H., Yu, C., Xu, H., Xu, S., Yang, C., Wang, F., Mi, H., and Shi, Y. Tactile compass: Enabling visually impaired people to follow a path with continuous directional feedback. In Proceedings from CHI 2021, 1--13.Google ScholarGoogle ScholarDigital LibraryDigital Library
  3. Shi, W., Yu, C., Fan, S., Wang, F., Wang, T., Yi, X., Bi, X., and Shi, Y. VIPBoard: Improving screen-reader keyboard for visually impaired people with character-level auto correction. In Proceedings from CHI 2019, 517.Google ScholarGoogle ScholarDigital LibraryDigital Library
  4. Song, S., Bu, J., Artmeier, A., Shi, K., Wang, Y., Yu, Z., and Wang, C. Crowdsourcing-based Web accessibility evaluation with golden maximum likelihood inference. In Proceedings of the 2018 ACM on Human-Computer Interaction, CSCW, 1--21.Google ScholarGoogle Scholar
  5. Song, S., Bu, J., Wang, Y., Yu, Z., Artmeier, A., Dai, L., and Wang, C. Web accessibility evaluation in a crowdsourcing-based system with expertise-based decision strategy. In Proceedings of the 2018 Internet of Accessible Things.Google ScholarGoogle Scholar
  6. Song, S., Bu, J., Shen, C., Artmeier, A., Yu, Z., and Zhou, Q. Reliability aware web accessibility experience metric. In Proceedings of the 2018 Internet of Accessible Things.Google ScholarGoogle Scholar
  7. Song, S., Wang, C., Li, L., Yu, Z., Lin, X., and Bu, J. WAEM: a web accessibility evaluation metric based on partial user experience order. In Proceedings of the 14th Web for All Conf. The Future of Accessible Work. (2017).Google ScholarGoogle ScholarDigital LibraryDigital Library
  8. Wang, R., Yu, C., Yang, X., He, W., and Shi, Y. EarTouch: Facilitating Smartphone use for visually impaired people in mobile and public scenarios. In Proceedings from CHI 2019, 24Google ScholarGoogle ScholarDigital LibraryDigital Library
  9. Wu, Z., Yu, C., Xu, X., Wei, T., Zou, T., Wang, R., and Shi, Y. LightWrite: Teach handwriting to the visually impaired with only a smartphone. Proceedings from CHI 2021, 1--15Google ScholarGoogle ScholarDigital LibraryDigital Library
  10. Xu, S., Yang, C., Ge, W., Yu, C., and Shi, Y. Virtual Paving: Rendering a smooth path for people with visual impairment through vibrotactile and audio feedback. In Proceedings of ACM Interact. Mob. Wearable Ubiquitous Technology 4, 4 (2020), 99:1--99:25.Google ScholarGoogle ScholarDigital LibraryDigital Library
  11. Yu, Z., Bu, J., Shen, C., Wang, W., Dai, L., Zhou, Q., and Zhao, C. A multi-site collaborative sampling for Web accessibility evaluation. In Proceedings of the Intern. Conf. Computers Helping People with Special Needs. Springer, Cham, 2020, 329--335.Google ScholarGoogle ScholarDigital LibraryDigital Library
  12. Zhang, M., Wang, C., Bu, J., Yu, Z., Lu, Y., Zhang, R., and Chen, C. An optimal sampling method for Web accessibility quantitative metric. In Proceedings of the 12th Web for All Conf. (2015).Google ScholarGoogle ScholarDigital LibraryDigital Library

Index Terms

  1. The practice of applying AI to benefit visually impaired people in China

        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

        Full Access

        • Published in

          cover image Communications of the ACM
          Communications of the ACM  Volume 64, Issue 11
          November 2021
          130 pages
          ISSN:0001-0782
          EISSN:1557-7317
          DOI:10.1145/3494050
          Issue’s Table of Contents

          Copyright © 2021 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 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]

          Publisher

          Association for Computing Machinery

          New York, NY, United States

          Publication History

          • Published: 25 October 2021

          Permissions

          Request permissions about this article.

          Request Permissions

          Check for updates

          Qualifiers

          • research-article
          • Popular
          • Refereed
        • Article Metrics

          • Downloads (Last 12 months)186
          • Downloads (Last 6 weeks)64

          Other Metrics

        PDF Format

        View or Download as a PDF file.

        PDF

        eReader

        View online with eReader.

        eReader

        HTML Format

        View this article in HTML Format .

        View HTML Format