Captioning for Deaf and Hard of Hearing People by Editing Automatic Speech Recognition in Real Time
Captioning for Deaf and Hard of Hearing People by Editing Automatic Speech Recognition in Real Time
Deaf and hard of hearing people can find it difficult to follow speech through hearing alone or to take notes when lip-reading or watching a sign-language interpreter. Notetakers summarise what is being said while qualified sign language interpreters with a good understanding of the relevant higher education subject content are in very scarce supply. Real time captioning/transcription is not normally available in UK higher education because of the shortage of real time stenographers. Lectures can be digitally recorded and replayed to provide multimedia revision material for students who attended the class and a substitute learning experience for students unable to attend. Automatic Speech Recognition can provide real time captioning directly from lecturers’ speech in classrooms but it is difficult to obtain accuracy comparable to stenography. This paper describes the development of a system that enables editors to correct errors in the captions as they are created by Automatic Speech Recognition.
683-690
Wald, M
90577cfd-35ae-4e4a-9422-5acffecd89d5
Miesenberger, K
dcee80ea-bb77-494c-9018-0ae09406e67d
July 2006
Wald, M
90577cfd-35ae-4e4a-9422-5acffecd89d5
Miesenberger, K
dcee80ea-bb77-494c-9018-0ae09406e67d
Wald, M
,
Miesenberger, K
(ed.)
(2006)
Captioning for Deaf and Hard of Hearing People by Editing Automatic Speech Recognition in Real Time.
Proceedings of 10th International Conference on Computers Helping People with Special Needs ICCHP 2006, LNCS 4061, .
Abstract
Deaf and hard of hearing people can find it difficult to follow speech through hearing alone or to take notes when lip-reading or watching a sign-language interpreter. Notetakers summarise what is being said while qualified sign language interpreters with a good understanding of the relevant higher education subject content are in very scarce supply. Real time captioning/transcription is not normally available in UK higher education because of the shortage of real time stenographers. Lectures can be digitally recorded and replayed to provide multimedia revision material for students who attended the class and a substitute learning experience for students unable to attend. Automatic Speech Recognition can provide real time captioning directly from lecturers’ speech in classrooms but it is difficult to obtain accuracy comparable to stenography. This paper describes the development of a system that enables editors to correct errors in the captions as they are created by Automatic Speech Recognition.
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Published date: July 2006
Organisations:
Web & Internet Science
Identifiers
Local EPrints ID: 262138
URI: http://eprints.soton.ac.uk/id/eprint/262138
PURE UUID: cdfdf7d3-f9cf-41b4-a943-235db5d859f7
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Date deposited: 24 Mar 2006
Last modified: 14 Mar 2024 07:06
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Contributors
Author:
M Wald
Editor:
K Miesenberger
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