Abstract
As a public service broadcaster the Βι¶ΉΤΌΕΔ strives to continually improve the quality of the services it provides to its audience. One service that has ongoing problems for our audience is live subtitling. This paper presents some candidate technologies to address the issues of timing, accuracy, and presentation in live subtitles. This work is motivated by research performed within Βι¶ΉΤΌΕΔ R&D to quantify the factors involved in subtitle quality and is at its early stages of development in the lab.
We started by looking at the challenge of improving the accuracy of subtitles and noticed that many errors were out of context from the programme topic. We chose as our target for research television weather forecasts as they usually use a constrained subset of the English language. The techniques we used attempted to capture the style of language used in weather forecasts by building a language model from a large body of known accurate subtitles. Once we had built the language model we used it for two purposes, firstly identifying the location of weather subtitles in larger news and magazine programmes and secondly identifying words within the weather subtitles which don't match the style of language.
Live subtitles arrive a few seconds late when broadcast but there is the opportunity to improve them for playback on demand. To improve the timing post broadcast we used a software text alignment tool to realign live subtitles. We also performed automatic reformatting of the subtitles to more closely match the Βι¶ΉΤΌΕΔ's subtitling guidelines. We will show the current performance of this technique and then briefly look at some novel forms of subtitle presentation achievable with audio aligned subtitles.
This paper was originally presented at the conference, Subtitling: A Collective Approach at the university of Nottingham.
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