Statistical multi-source translation

Franz Josef Och, Hermann Ney


Abstract
We describe methods for translating a text given in multiple source languages into a single target language. The goal is to improve translation quality in applications where the ultimate goal is to translate the same document into many languages. We describe a statistical approach and two specific statistical models to deal with this problem. Our method is generally applicable as it is independent of specific models, languages or application domains. We evaluate the approach on a multilingual corpus covering all eleven official European Union languages that was collected automatically from the Internet. In various tests we show that these methods can significantly improve translation quality. As a side effect, we also compare the quality of statistical machine translation systems for many European languages in the same domain.
Anthology ID:
2001.mtsummit-papers.46
Volume:
Proceedings of Machine Translation Summit VIII
Month:
September 18-22
Year:
2001
Address:
Santiago de Compostela, Spain
Editor:
Bente Maegaard
Venue:
MTSummit
SIG:
Publisher:
Note:
Pages:
Language:
URL:
https://aclanthology.org/2001.mtsummit-papers.46
DOI:
Bibkey:
Cite (ACL):
Franz Josef Och and Hermann Ney. 2001. Statistical multi-source translation. In Proceedings of Machine Translation Summit VIII, Santiago de Compostela, Spain.
Cite (Informal):
Statistical multi-source translation (Och & Ney, MTSummit 2001)
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PDF:
https://preview.aclanthology.org/emnlp22-frontmatter/2001.mtsummit-papers.46.pdf