Enhancement of Learning using Speech Recognition and Lecture Transcription: A Survey

2014 
Speech recognition (SR) technologies were evaluated in different classroom environments to assist students to automatically convert oral lectures into text. Two distinct methods of SR-mediated lecture acquisition (SR-mLA), realtime captioning (RTC) and post-lecture transcription (PLT), has been developed to increase the word recognition accuracy. Both methods has been compared according to technical feasibility and reliability of classroom implementation, instructors‟ experiences, word recognition accuracy, and student class performance. RTC provided near-instantaneous display of the instructor‟s speech for students during class. PLT employed a user-independent SR algorithm to optimally generate multimedia class notes with synchronized lecture transcripts and instructor audio for students to access online after class. It has been learnt that PLT provides more word recognition accuracy than RTC. The potential benefits of SRmLA for students who have difficulty taking notes accurately and independently were discussed, particularly for non-native English speakers and students with disabilities.
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