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International Conference on Intelligent Text Processing and Computational Linguistics

CICLing 2016: Computational Linguistics and Intelligent Text Processing pp 127–139Cite as

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

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Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 9624))

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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Notes

  1. 1.

    https://www.amara.org/en/.

  2. 2.

    The data can be found at http://workshop2013.iwslt.org.

  3. 3.

    For a broader discussion see also [6, 21].

  4. 4.

    This is the official scoring method for the translation tracks into Arabic at IWSLT’13: http://alt.qcri.org/tools/arabic-normalizer.

  5. 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.

  6. 6.

    https://wit3.fbk.eu.

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Authors and Affiliations

  1. Qatar Computing Research Institute, HBKU, Doha, Qatar

    Fahad Al-Obaidli & Preslav Nakov

  2. School of Computing Sciences, University of East Anglia, Norwich, UK

    Stephen Cox

Authors
  1. Fahad Al-Obaidli
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  2. Stephen Cox
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  3. Preslav Nakov
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Correspondence to Preslav Nakov .

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Editors and Affiliations

  1. CIC, Instituto Politécnico Nacional, Mexico City, Mexico

    Alexander Gelbukh

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Al-Obaidli, F., Cox, S., Nakov, P. (2018). Bi-text Alignment of Movie Subtitles for Spoken English-Arabic Statistical Machine Translation. In: Gelbukh, A. (eds) Computational Linguistics and Intelligent Text Processing. CICLing 2016. Lecture Notes in Computer Science(), vol 9624. Springer, Cham. https://doi.org/10.1007/978-3-319-75487-1_11

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

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