Yota Georgakopoulou
2019
Customizing Neural Machine Translation for Subtitling
Evgeny Matusov
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Patrick Wilken
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Yota Georgakopoulou
Proceedings of the Fourth Conference on Machine Translation (Volume 1: Research Papers)
In this work, we customized a neural machine translation system for translation of subtitles in the domain of entertainment. The neural translation model was adapted to the subtitling content and style and extended by a simple, yet effective technique for utilizing inter-sentence context for short sentences such as dialog turns. The main contribution of the paper is a novel subtitle segmentation algorithm that predicts the end of a subtitle line given the previous word-level context using a recurrent neural network learned from human segmentation decisions. This model is combined with subtitle length and duration constraints established in the subtitling industry. We conducted a thorough human evaluation with two post-editors (English-to-Spanish translation of a documentary and a sitcom). It showed a notable productivity increase of up to 37% as compared to translating from scratch and significant reductions in human translation edit rate in comparison with the post-editing of the baseline non-adapted system without a learned segmentation model.
2017
TraMOOC: Translation for Massive Open Online Courses
Joss Moorkens
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Yota Georgakopoulou
Proceedings of Machine Translation Summit XVI: Commercial MT Users and Translators Track
2013
New tools for subtitle translation
Yota Georgakopoulou
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Lindsay Bywood
Proceedings of Translating and the Computer 35
2012
From Subtitles to Parallel Corpora
Mark Fishel
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Yota Georgakopoulou
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Sergio Penkale
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Volha Petukhova
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Matej Rojc
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Martin Volk
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Andy Way
Proceedings of the 16th Annual conference of the European Association for Machine Translation
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Co-authors
- Lindsay Bywood 1
- Mark Fishel 1
- Sergio Penkale 1
- Volha Petukhova 1
- Matej Rojc 1
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