Communication Access Real-Time Translation Through Collaborative Correction of Automatic Speech Recognition

Fuente: arXiv
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Hauptverfasser: Kuhn, Korbinian, Kersken, Verena, Zimmermann, Gottfried
Format: Preprint
Veröffentlicht: 2025
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author Kuhn, Korbinian
Kersken, Verena
Zimmermann, Gottfried
author_facet Kuhn, Korbinian
Kersken, Verena
Zimmermann, Gottfried
contents Communication access real-time translation (CART) is an essential accessibility service for d/Deaf and hard of hearing (DHH) individuals, but the cost and scarcity of trained personnel limit its availability. While Automatic Speech Recognition (ASR) offers a cheap and scalable alternative, transcription errors can lead to serious accessibility issues. Real-time correction of ASR by non-professionals presents an under-explored CART workflow that addresses these limitations. We conducted a user study with 75 participants to evaluate the feasibility and efficiency of this workflow. Complementary, we held focus groups with 25 DHH individuals to identify acceptable accuracy levels and factors affecting the accessibility of real-time captioning. Results suggest that collaborative editing can improve transcription accuracy to the extent that DHH users rate it positively regarding understandability. Focus groups also showed that human effort to improve captioning is highly valued, supporting a semi-automated approach as an alternative to stand-alone ASR and traditional CART services.
format Preprint
id arxiv_https___arxiv_org_abs_2503_15120
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Communication Access Real-Time Translation Through Collaborative Correction of Automatic Speech Recognition
Kuhn, Korbinian
Kersken, Verena
Zimmermann, Gottfried
Human-Computer Interaction
Sound
Audio and Speech Processing
I.2.7
Communication access real-time translation (CART) is an essential accessibility service for d/Deaf and hard of hearing (DHH) individuals, but the cost and scarcity of trained personnel limit its availability. While Automatic Speech Recognition (ASR) offers a cheap and scalable alternative, transcription errors can lead to serious accessibility issues. Real-time correction of ASR by non-professionals presents an under-explored CART workflow that addresses these limitations. We conducted a user study with 75 participants to evaluate the feasibility and efficiency of this workflow. Complementary, we held focus groups with 25 DHH individuals to identify acceptable accuracy levels and factors affecting the accessibility of real-time captioning. Results suggest that collaborative editing can improve transcription accuracy to the extent that DHH users rate it positively regarding understandability. Focus groups also showed that human effort to improve captioning is highly valued, supporting a semi-automated approach as an alternative to stand-alone ASR and traditional CART services.
title Communication Access Real-Time Translation Through Collaborative Correction of Automatic Speech Recognition
topic Human-Computer Interaction
Sound
Audio and Speech Processing
I.2.7
url https://arxiv.org/abs/2503.15120