Large aligned treebanks for syntax-based machine translation

KOTZÉ, Gideon, Vincent VANDEGHINSTE, Scott MARTENS and Jörg TIEDEMANN. Large aligned treebanks for syntax-based machine translation. LANGUAGE RESOURCES AND EVALUATION. NETHERLANDS: SPRINGER, 2017, Vol. 51(2), p. 249-282. ISSN 1574-020X. Available from: https://dx.doi.org/10.1007/s10579-016-9369-0.

Basic information

Original name

Large aligned treebanks for syntax-based machine translation

Authors

KOTZÉ, Gideon, Vincent VANDEGHINSTE, Scott MARTENS and Jörg TIEDEMANN

Edition

LANGUAGE RESOURCES AND EVALUATION, NETHERLANDS, SPRINGER, 2017, 1574-020X

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Other information

Type of outcome

Článek v odborném periodiku

Confidentiality degree

není předmětem státního či obchodního tajemství

Impact factor

Impact factor: 0.656

DOI

http://dx.doi.org/10.1007/s10579-016-9369-0

Keywords in English

parallel treebank, parallel corpus, machine translation, syntax-based machine translation, constituent alignment, tree alignment, resource development

Tags

constituent alignment, machine translation, parallel corpus, parallel treebank, Pouze vystaveno, resource development, syntax-based machine translation, tree alignment

Tags

International impact, Reviewed

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Abstract

V originále

We present a collection of parallel treebanks that have been automatically aligned on both the terminal and the non-terminal constituent level for use in syntax-based machine translation. We describe how they were constructed and applied to a syntax- and example-based machine translation system called Parse and Corpus-Based Machine Translation (PaCo-MT). For the language pair Dutch to English, we present non-terminal alignment evaluation scores for a variety of tree alignment approaches. Finally, based on the parallel treebanks created by these approaches, we evaluate the MT system itself and compare the scores with those of Moses, a current state-of-the-art statistical MT system, when trained on the same data.