What Speech Recognition Accuracy is Needed for Video Transcripts to be a Useful Search Interface?

Abstract

Informative videos (e.g. recorded lectures) are increasingly being made available online, but they are difficult to use, browse and search. Nowadays, popular platforms let users search and navigate videos via a transcript, which, in order to guarantee a satisfactory level of word accuracy, has typically been generated using some manual inputs. The goal of our work is to try and take a step closer to the fully automatic generation of informative video transcripts based on current automatic speech recognition technology. We present a user study designed to better understand viewers’ use of video transcripts for searching a video content, with the aim of estimating what minimum word recognition accuracy is needed for video captions to be a useful search interface. We found that transcripts with 70% word recognition accuracy are as effective as 100% accuracy transcripts in supporting video search when using single word search. We also found that there are large variations in the time it takes to search a video, independently of the quality of the transcript. With adequate and adapted search strategies, even low accuracy transcripts can support quick video search.