scholarly journals Captioning for Deaf and Hard of Hearing People by Editing Automatic Speech Recognition in Real Time

2006 ◽  
pp. 683-690 ◽  
Author(s):  
Mike Wald
Keyword(s):  
Speech Recognition ◽  
Real Time ◽  
Automatic Speech Recognition ◽  
Hard Of Hearing

Real-time integration of dynamic context information for improving automatic speech recognition

2015 ◽  
Author(s):  
Youssef Oualil ◽  
Marc Schulder ◽  
Hartmut Helmke ◽  
Anna Schmidt ◽  
Dietrich Klakow
Keyword(s):  
Speech Recognition ◽  
Real Time ◽  
Automatic Speech Recognition ◽  
Time Integration ◽  
Context Information ◽  
Dynamic Context

Automatic Speech Recognition to Enhance Learning for Disabled Students

2011 ◽  
pp. 89-104 ◽  
Author(s):  
Pablo Revuelta ◽  
Javier Jiménez ◽  
José M. Sánchez ◽  
Belén Ruiz
Keyword(s):  
Speech Recognition ◽  
Real Time ◽  
Inclusive Education ◽  
Automatic Speech Recognition ◽  
Communication Technology ◽  
Note Taking ◽  
Disabled People ◽  
Disabled Students ◽  
The World ◽  
Information And Communication

This chapter introduces the potential of Automatic Speech Recognition Technology (ASR) in the challenge of inclusive education. ASR technology combined with Information and Communication Technology (ICT) enhances the learning of disabled people both in and outside the classroom. In the classroom, deaf and hearing-impaired students can benefit from a real-time transcription of what the teacher is saying. Also, a real-time transcription facilitates note taking for students with visual or physical disabilities. Outside the classroom, transcription and other media files (audio, slides, video, etc.) are powerful educational resources for all students, disabled or able-bodied. Some of most relevant projects and systems around the world are described and compared in this chapter to provide updated information about ASR technology performance and its application to enhancing the learning of disabled students.

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