Yota Georgakopoulou


Customizing Neural Machine Translation for Subtitling
Evgeny Matusov | Patrick Wilken | 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.


TraMOOC: Translation for Massive Open Online Courses
Joss Moorkens | Yota Georgakopoulou
Proceedings of Machine Translation Summit XVI: Commercial MT Users and Translators Track


New tools for subtitle translation
Yota Georgakopoulou | Lindsay Bywood
Proceedings of Translating and the Computer 35


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From Subtitles to Parallel Corpora
Mark Fishel | Yota Georgakopoulou | Sergio Penkale | Volha Petukhova | Matej Rojc | Martin Volk | Andy Way
Proceedings of the 16th Annual conference of the European Association for Machine Translation