Literature Reviews
Reviewed research papers, articles, and publications relevant to digital accessibility.
46 results found tagged automatic speech recognition.
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Measuring the Accuracy of Automatic Speech Recognition Solutions
This study provides independent, comprehensive benchmarking of 11 common automatic speech recognition (ASR) services to assess their real-world accuracy for accessibility purposes. The research addresses a critical gap: while vendors claim "state-of-…
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Evaluating Alternatives for Better Deaf Accessibility to Selected Web-Based Multimedia
This research addresses the accessibility gap created by the proliferation of uncaptioned video content online—a particular problem for deaf adults who use American Sign Language as their primary language and view English as a second language. While …
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The Effects of Automatic Speech Recognition Quality on Human Transcription Latency
This paper investigates a practical question for accessibility: when does providing automatic speech recognition (ASR) output help human captionists work faster, and when does it slow them down? Converting speech to text is fundamental for making aud…
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Improving Real-Time Captioning Experiences for Deaf and Hard of Hearing Students
This paper takes a holistic, qualitative approach to understanding deaf and hard of hearing (DHH) university students' experiences with real-time captioning in mainstream classrooms, examining both human-based captioning (CART — Communication Access …
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Deaf and Hard-of-Hearing Perspectives on Imperfect Automatic Speech Recognition for Captioning One-on-One Meetings
This paper investigates whether and how to display word-level confidence information from Automatic Speech Recognition (ASR) systems in real-time captions for Deaf and Hard-of-Hearing (DHH) users during one-on-one meetings with hearing people. ASR en…
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Evaluating the Usability of Automatically Generated Captions for People who are Deaf or Hard of Hearing
This paper addresses a fundamental problem in automatic captioning for Deaf and Hard of Hearing (DHH) users: the standard metric used to evaluate automatic speech recognition (ASR) systems — Word Error Rate (WER) — poorly predicts how usable the resu…
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Deaf, Hard of Hearing, and Hearing Perspectives on Using Automatic Speech Recognition in Conversation
This experience report describes the real-world accessibility challenges encountered by five participants — two deaf, one hard of hearing, and two hearing — including the authors, when using the top seven most popular ASR applications (DEAFCOM, Drago…
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Personal Perspectives on Using Automatic Speech Recognition to Facilitate Communication between Deaf Students and Hearing Customers
This experience report examines the use of Automatic Speech Recognition (ASR) via the WhatsApp smartphone app to facilitate communication between deaf and hard-of-hearing (D/HH) students and hearing business customers in real workplace settings. The …
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Towards More Robust Speech Interactions for Deaf and Hard of Hearing Users
This University of Michigan study addresses a largely overlooked accessibility gap: while much research has focused on providing deaf users access to spoken output (via captioning or sign language), almost no work has addressed improving deaf users' …
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Behavioral Changes in Speakers who are Automatically Captioned in Meetings with Deaf or Hard-of-Hearing Peers
This study from Rochester Institute of Technology investigates a largely unexplored question: how does using an ASR-based captioning tool in meetings with deaf or hard of hearing (DHH) colleagues change the speaking behavior of hearing participants? …