A crowdsourcing caption editor for educational videos
Rucha Deshpande, Tayfun Tuna, Jaspal Subhlok, Lecia Jane Barker · 2014
Video of a classroom lecture has been shown to be a versatile learning resource comparable to a textbook. Captions in videos are highly valued by students, especially those with hearing disability and those whose first language is not English. Captioning by automatic speech recognition (ASR) tools is of limited use because of low and variable accuracy. Manual captioning with existing tools is a slow, tedious and expensive task. In this work, we present a web-based crowdsourcing editor to add or correct captions for video lectures. The editor allows a group, e.g., students in a class, to correct the captions for different parts of a video lecture simultaneously. Users can review and correct each other's work. The caption editor has been successfully employed to caption STEM coursework videos. Our findings based on survey results and interviews indicate that this innovative crowdsourcing tool is effective and efficient for captioning lecture videos and has considerable value in educational practice. The caption editor is integrated with Indexed Captioned Searchable (ICS) Videos framework at University of Houston that has been used by dozens of courses and 1000s of students. The ICS Videos framework including the captioning tool is open source software available to educational institutions.