Critical Success Factors for Automatic Speech Recognition in the Classroom

Bennett, Steven; Hewitt, Jill; Mellor, Barry; Lyon, Caroline

doi:10.1007/978-3-540-73283-9_26

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Automatic Speech Recognition Captioning1

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2010

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“…<15% word error rate). Similar results have been reported by others using the Microsoft SR Engine [12] or Dragon [13]. To improve accuracy and understanding of SR captions an application RealTimeEdit was developed to enable corrections of SR captions to be made in real-time [14].…”

Section: Automatic Speech Recognition Captioningsupporting

confidence: 49%

Synote: Accessible and Assistive Technology Enhancing Learning for All Students

Wald

2010

Lecture Notes in Computer Science

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Abstract. Although manual transcription and captioning can increase the accessibility of multimedia for deaf students it is rarely provided in educational contexts in the UK due to the cost and shortage of highly skilled and trained stenographers. Speech recognition has the potential to reduce the cost and increase the availability of captioning if it could satisfy accuracy and readability requirements. This paper discusses how Synote, a web application for annotating and captioning multimedia, can enhance learning for all students and how, finding ways to improve the accuracy and readability of automatic captioning, can encourage its widespread adoption and so greatly benefit disabled students.

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Section: Automatic Speech Recognition Captioningsupporting

confidence: 49%

Synote: Accessible and Assistive Technology Enhancing Learning for All Students

Wald

2010

Lecture Notes in Computer Science

View full text Add to dashboard Cite

show abstract

Critical Success Factors for Automatic Speech Recognition in the Classroom

Cited by 1 publication

References 1 publication

Synote: Accessible and Assistive Technology Enhancing Learning for All Students

Synote: Accessible and Assistive Technology Enhancing Learning for All Students

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