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• Artificial Intelligence Fairness in the Context of Accessibility Research on Intelligent Systems for People Who Are Deaf or Hard of Hearing

  Sushant Kafle, Abraham Glasser, Sedeeq Al-khazraji, Larwan Berke, Matthew Seita, Matt Huenerfauth · 2020 · SIGACCESS Accessibility and Computing

  This paper from RIT's Center for Accessibility and Inclusion Research discusses AI fairness issues specifically through the lens of the authors' extensive research on intelligent systems for people who are Deaf or Hard of Hearing (DHH). The authors identify five interconnected…

  AI fairness · deaf and hard of hearing · automatic speech recognition · captioning · evaluation metrics

• Deaf and hard-of-hearing users’ prioritization of genres of online video content requiring accurate captions

  Larwan Berke, Matthew Seita, Matt Huenerfauth · 2020 · Proceedings of the 17th International Web for All Conference (W4A)

  This paper investigates which genres of online video content Deaf and Hard-of-Hearing (DHH) users consider most important to have accurately captioned. With over 400 hours of video uploaded to YouTube every minute and no U.S. legal mandate to caption all online video (especially…

  deaf and hard of hearing · captioning · video accessibility · automatic speech recognition · user research

• Breaking Boundaries with Live Transcribe: Expanding Use Cases Beyond Standard Captioning Scenarios

  Fernando Loizides, Sara Basson, Dimitri Kanevsky, Olga Prilepova, Sagar Savla, Susanna Zaraysky · 2020 · Proceedings of the 22nd International ACM SIGACCESS Conference on Computers and Accessibility (ASSETS)

  This short paper catalogs non-traditional, serendipitous uses of Google's Live Transcribe, a free Android application that provides real-time speech-to-text transcription in over 80 languages. The authors — a mix of Google developers, researchers, and DHH users (co-creator…

  automatic speech recognition · deaf and hard of hearing · captioning · speech to text · COVID-19

• Deaf Individuals' Views on Speaking Behaviors of Hearing Peers when Using an Automatic Captioning App

  Matthew Seita, Matt Huenerfauth · 2020 · Extended Abstracts of the 2020 CHI Conference on Human Factors in Computing Systems (CHI EA '20)

  This CHI 2020 Late-Breaking Work paper investigates what behaviors hearing speakers should ideally exhibit when holding in-person conversations with Deaf or deaf people using an Automatic Speech Recognition (ASR) captioning app on a mobile device. The authors position the study…

  automatic speech recognition · deaf and hard of hearing · captioning · captions · speaking behavior

• Accessibility for Deaf and Hard of Hearing Users: Sign Language Conversational User Interfaces

  Abraham Glasser, Vaishnavi Mande, Matt Huenerfauth · 2020 · Proceedings of the 2nd Conference on Conversational User Interfaces (CUI '20)

  This short CUI 2020 position paper (3 pages, presented at the CUI@CHI workshop) lays out the research agenda for making voice-based conversational user interfaces (CUIs) — Alexa, Google Assistant, and similar personal assistant devices — accessible to Deaf and Hard-of-Hearing…

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

5 results.