Customizing Neural Machine Translation for Subtitling

Evgeny Matusov, Patrick Wilken, Yota Georgakopoulou


Abstract
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.
Anthology ID:
W19-5209
Volume:
Proceedings of the Fourth Conference on Machine Translation (Volume 1: Research Papers)
Month:
August
Year:
2019
Address:
Florence, Italy
Editors:
Ondřej Bojar, Rajen Chatterjee, Christian Federmann, Mark Fishel, Yvette Graham, Barry Haddow, Matthias Huck, Antonio Jimeno Yepes, Philipp Koehn, André Martins, Christof Monz, Matteo Negri, Aurélie Névéol, Mariana Neves, Matt Post, Marco Turchi, Karin Verspoor
Venue:
WMT
SIG:
SIGMT
Publisher:
Association for Computational Linguistics
Note:
Pages:
82–93
Language:
URL:
https://aclanthology.org/W19-5209
DOI:
10.18653/v1/W19-5209
Bibkey:
Cite (ACL):
Evgeny Matusov, Patrick Wilken, and Yota Georgakopoulou. 2019. Customizing Neural Machine Translation for Subtitling. In Proceedings of the Fourth Conference on Machine Translation (Volume 1: Research Papers), pages 82–93, Florence, Italy. Association for Computational Linguistics.
Cite (Informal):
Customizing Neural Machine Translation for Subtitling (Matusov et al., WMT 2019)
Copy Citation:
PDF:
https://aclanthology.org/W19-5209.pdf
Data
OpenSubtitles