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• Exploring Collection of Sign Language Datasets: Privacy, Participation, and Model Performance

  Danielle Bragg, Oscar Koller, Naomi Caselli, William Thies · 2020 · Proceedings of the 22nd International ACM SIGACCESS Conference on Computers and Accessibility (ASSETS 2020)

  This paper tackles a fundamental tension in building machine learning systems for marginalized communities: the need for large training datasets versus the privacy risks of collecting data from small, identifiable populations. The authors focus on sign language video collection,…

  sign language · privacy · machine learning · data collection · Deaf culture

• Creating questionnaires that align with ASL linguistic principles and cultural practices within the Deaf community

  Rachel Boll, Shruti Mahajan, Jeanne Reis, Erin T. Solovey · 2020 · ACM SIGACCESS Conference on Computers and Accessibility (ASSETS)

  This poster paper from Worcester Polytechnic Institute and The Learning Center for the Deaf addresses a fundamental gap in HCI research methodology: most interactive computing tools, including survey and questionnaire platforms, are designed exclusively for text and written…

  deaf · American Sign Language · questionnaire design · research methods · Deaf culture

• Sign Language Interfaces: Discussing the Field's Biggest Challenges

  Danielle Bragg, Meredith Ringel Morris, Christian Vogler, Raja Kushalnagar, Matt Huenerfauth, Hernisa Kacorri · 2020 · Extended Abstracts of the 2020 CHI Conference on Human Factors in Computing Systems (CHI EA '20)

  This CHI 2020 Special Interest Group (SIG) meeting paper (5 pages) is an organising document rather than a conventional research paper. It convenes HCI and accessibility researchers working on sign-language interfaces around the five calls-to-action laid out in Bragg et al.’s…

  sign language · deaf and hard of hearing · deaf culture · american sign language · research methodology

3 results.