Improving the Quality of Automated DVD Subtitles via Example-Based Machine Translation (2006)
| Citations: | 3 - 0 self |
BibTeX
@MISC{Armstrong06improvingthe,
author = {Stephen Armstrong and Andy Way and Colm Caffrey and Marian Flanagan and Dorothy Kenny},
title = {Improving the Quality of Automated DVD Subtitles via Example-Based Machine Translation},
year = {2006}
}
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Abstract
Denoual (2005) discovered that, contrary to popular belief, an EBMT system trained on heterogeneous data produced significantly better results than a system trained on homogeneous data. Using similar evaluation metrics and a few additional ones, in this paper we show that this does not hold true for the automated translation of subtitles. In fact, our system (when trained on homogeneous data) shows a relative increase of 74 % BLEU in the language direction German-English and 86 % BLEU English-German. Furthermore, we show that increasing the amount of heterogeneous data results in ‘bad examples ’ being put forward as translation candidates, thus lowering the translation quality. 1
