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Enabling Medical Translation for Low-Resource Languages Read chapter Read first chapter

2018 | OriginalPaper | Chapter

Bi-text Alignment of Movie Subtitles for Spoken English-Arabic Statistical Machine Translation

Authors : Fahad Al-Obaidli, Stephen Cox, Preslav Nakov

Published in: Computational Linguistics and Intelligent Text Processing

Publisher: Springer International Publishing

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Abstract

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.

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Footnotes
2
The data can be found at http://​workshop2013.​iwslt.​org.
 
3
For a broader discussion see also [6, 21].
 
4
This is the official scoring method for the translation tracks into Arabic at IWSLT’13: http://​alt.​qcri.​org/​tools/​arabic-normalizer.
 
5
We set M to be at most 5 in order to prevent the algorithm from unreasonably iterating up to the last segment looking for a match.
 
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Metadata
Title
Bi-text Alignment of Movie Subtitles for Spoken English-Arabic Statistical Machine Translation
Authors
Fahad Al-Obaidli
Stephen Cox
Preslav Nakov
Copyright Year
2018
Book
Computational Linguistics and Intelligent Text Processing

Print ISBN: 978-3-319-75486-4

Electronic ISBN: 978-3-319-75487-1

Copyright Year: 2018

DOI
https://doi.org/10.1007/978-3-319-75487-1_11

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