A Richly Annotated, Multilingual Parallel Corpus for Hybrid Machine Translation

Eleftherios Avramidis, Marta R. Costa-jussà, Christian Federmann, Josef van Genabith, Maite Melero, Pavel Pecina


Abstract
In recent years, machine translation (MT) research has focused on investigating how hybrid machine translation as well as system combination approaches can be designed so that the resulting hybrid translations show an improvement over the individual “component” translations. As a first step towards achieving this objective we have developed a parallel corpus with source text and the corresponding translation output from a number of machine translation engines, annotated with metadata information, capturing aspects of the translation process performed by the different MT systems. This corpus aims to serve as a basic resource for further research on whether hybrid machine translation algorithms and system combination techniques can benefit from additional (linguistically motivated, decoding, and runtime) information provided by the different systems involved. In this paper, we describe the annotated corpus we have created. We provide an overview on the component MT systems and the XLIFF-based annotation format we have developed. We also report on first experiments with the ML4HMT corpus data.
Anthology ID:
L12-1231
Volume:
Proceedings of the Eighth International Conference on Language Resources and Evaluation (LREC'12)
Month:
May
Year:
2012
Address:
Istanbul, Turkey
Editors:
Nicoletta Calzolari, Khalid Choukri, Thierry Declerck, Mehmet Uğur Doğan, Bente Maegaard, Joseph Mariani, Asuncion Moreno, Jan Odijk, Stelios Piperidis
Venue:
LREC
SIG:
Publisher:
European Language Resources Association (ELRA)
Note:
Pages:
2189–2193
Language:
URL:
http://www.lrec-conf.org/proceedings/lrec2012/pdf/444_Paper.pdf
DOI:
Bibkey:
Cite (ACL):
Eleftherios Avramidis, Marta R. Costa-jussà, Christian Federmann, Josef van Genabith, Maite Melero, and Pavel Pecina. 2012. A Richly Annotated, Multilingual Parallel Corpus for Hybrid Machine Translation. In Proceedings of the Eighth International Conference on Language Resources and Evaluation (LREC'12), pages 2189–2193, Istanbul, Turkey. European Language Resources Association (ELRA).
Cite (Informal):
A Richly Annotated, Multilingual Parallel Corpus for Hybrid Machine Translation (Avramidis et al., LREC 2012)
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PDF:
http://www.lrec-conf.org/proceedings/lrec2012/pdf/444_Paper.pdf