Paper: Text Alignment for Real-Time Crowd Captioning

ACL ID N13-1020
Title Text Alignment for Real-Time Crowd Captioning
Venue Annual Conference of the North American Chapter of the Association for Computational Linguistics
Session Main Conference
Year 2013
Authors

The primary way of providing real-time cap- tioning for deaf and hard of hearing people is to employ expensive professional stenogra- phers who can type as fast as natural speak- ing rates. Recent work has shown that a feasible alternative is to combine the partial captions of ordinary typists, each of whom types part of what they hear. In this paper, we describe an improved method for combin- ing partial captions into a final output based on weighted A? search and multiple sequence alignment (MSA). In contrast to prior work, our method allows the tradeoff between accu- racy and speed to be tuned, and provides for- mal error bounds. Our method outperforms the current state-of-the-art on Word Error Rate (WER) (29.6%), BLEU Score (41.4%), and F-measure (36.9%). The end goal is for these capt...