We describe efforts towards getting better resources for English-Arabic machine translation of spoken text. In particular, we look at movie subtitles as a unique, rich resource, as subtitles in one language often get translated into other languages. Movie subtitles are not new as a resource and have been explored in previous research; however, here we create a much larger bi-text (the biggest to date), and we further generate better quality alignment for it. Given the subtitles for the same movie in different languages, a key problem is how to align them at the fragment level. Typically, this is done using length-based alignment, but for movie subtitles, there is also time information. Here we exploit this information to develop an original algorithm that outperforms the current best subtitle alignment tool, subalign. The evaluation results show that adding our bi-text to the IWSLT training bi-text yields an improvement of over two BLEU points absolute.
For alignment, Tiedemann, started with the traditional approach of length-based sentence alignment @cite_16 using sentence boundaries tagged in an earlier stage. This is based on the idea that sentences are linguistically-driven elements and, thus, it would be more appropriate to process them using linguistic features rather than merely aligning subtitles appearing simultaneously on the screen. Nonetheless, there are many untranslated parts of the movie for reasons discussed earlier. The initial results were unsatisfactory.
@cite_16
1533246198
Sentence alignment is an essential step in building a parallel corpus. In this paper a specialized approach for the alignment of movie subtitles based on time overlaps is introduced. It is used for creating an extensive multilingual parallel subtitle corpus currently containing about 21 million aligned sentence fragments in 29 languages. Our alignment approach yields significantly higher accuracies compared to standard length-based approaches on this data. Furthermore, we can show that simple heuristics for subtitle synchronization can be used to improve the alignment accuracy even further.