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• Understanding Deaf and Hard-of-Hearing Users' Interest in Sign-Language Interaction with Personal-Assistant Devices

  Abraham Glasser, Vaishnavi Mande, Matt Huenerfauth · 2021 · Proceedings of the 18th International Web for All Conference (W4A '21)

  This mixed-methods study investigates Deaf and Hard of Hearing (DHH) users' experiences with and interest in personal-assistant devices (such as Amazon Alexa and Google Home) that could understand American Sign Language (ASL) commands. The research was motivated by the growing…

  deaf and hard of hearing · sign language · personal assistants · voice interface · smart home

• I See What You're Saying: A Literature Review of Eye Tracking Research in Communication of Deaf or Hard of Hearing Users

  Chanchal Agrawal, Roshan L Peiris · 2021 · Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (ASSETS '21)

  This paper presents a comprehensive literature review of 55 eye-tracking studies examining the gaze patterns and communication behaviours of deaf or hard-of-hearing (DHH) individuals. The authors systematically searched ACM, IEEE, Google Scholar, and linguistics and psychology…

  deaf and hard of hearing · eye tracking · eye gaze · sign language · lip-reading

• Lost in Translation: Challenges and Barriers to Sign Language-Accessible User Research

  Amelie Unger, Dieter P. Wallach, Nicole Jochems · 2021 · Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (ASSETS '21)

  This experience report describes the challenges hearing researchers face when conducting user research with sign language (SL) users, based on the authors' experience running remote focus groups with German Sign Language (GSL) users as part of the AVASAG project — which is…

  deaf and hard of hearing · sign language · user research · focus groups · language accessibility

• American Sign Language Video Anonymization to Support Online Participation of Deaf and Hard of Hearing Users

  Sooyeon Lee, Abraham Glasser, Becca Dingman, Zhaoyang Xia, Dimitris Metaxas, Carol Neidle, Matt Huenerfauth · 2021 · ASSETS '21: The 23rd International ACM SIGACCESS Conference on Computers and Accessibility

  Deaf and Hard of Hearing (DHH) individuals who prefer to communicate in American Sign Language (ASL) face a unique privacy barrier online: because ASL is a visual language conveyed through movements of the face, head, hands, and torso, and because the face carries essential…

  deaf and hard of hearing · sign language · American Sign Language · anonymization · privacy

• Deep Learning Methods for Sign Language Translation

  Tejaswini Ananthanarayana, Priyanshu Srivastava, Akash Chintha, Akhil Santha, Brian Landy, Joseph Panaro, Andre Webster, Nikunj Kotecha, Shagan Sah, Thomastine Sarchet, Raymond Ptucha, Ifeoma Nwogu · 2021 · ACM Transactions on Accessible Computing

  This comprehensive study evaluates deep learning methods for translating sign language video directly to spoken/written text—critically, without requiring the intermediate step of gloss-based recognition (manual sign-for-sign transcription). The researchers systematically…

  sign language · machine translation · deep learning · transformer · neural network

• The FATE Landscape of Sign Language AI Datasets: An Interdisciplinary Perspective

  Danielle Bragg, Oscar Koller, Mary Bellard, Larwan Berke, Patrick Boudreault, Annelies Braffort, Naomi Caselli, Matt Huenerfauth, Hernisa Kacorri, Tessa Verhoef, Christian Vogler, Meredith Ringel Morris · 2021 · ACM Transactions on Accessible Computing

  This interdisciplinary paper examines the ethical landscape of AI datasets used for sign language recognition, generation, and translation technologies. Drawing on expertise from deaf community members, sign language linguists, and AI researchers, the authors apply the FATE…

  sign language · AI datasets · deaf community · FATE framework · machine learning

• Deaf Users' Preferences Among Wake-Up Approaches during Sign-Language Interaction with Personal Assistant Devices

  Vaishnavi Mande, Abraham Glasser, Becca Dingman, Matt Huenerfauth · 2021 · Extended Abstracts of the 2021 CHI Conference on Human Factors in Computing Systems (CHI EA '21)

  This CHI 2021 Extended Abstract investigates a narrow but previously unexplored question: if future personal-assistant devices (Alexa, Google Assistant, etc.) could recognise sign language, how should Deaf users wake them up? Current wake-up mechanisms — speaking a wake-word…

  deaf and hard of hearing · sign language · personal assistants · voice interface · conversational user interfaces

7 results.