@inproceedings{tiedemann-etal-2012-distributed,
title = "A Distributed Resource Repository for Cloud-Based Machine Translation",
author = {Tiedemann, J{\"o}rg and
Hansen, Dorte Haltrup and
Offersgaard, Lene and
Olsen, Sussi and
Zumpe, Matthias},
editor = "Calzolari, Nicoletta and
Choukri, Khalid and
Declerck, Thierry and
Do{\u{g}}an, Mehmet U{\u{g}}ur and
Maegaard, Bente and
Mariani, Joseph and
Moreno, Asuncion and
Odijk, Jan and
Piperidis, Stelios",
booktitle = "Proceedings of the Eighth International Conference on Language Resources and Evaluation ({LREC}'12)",
month = may,
year = "2012",
address = "Istanbul, Turkey",
publisher = "European Language Resources Association (ELRA)",
url = "http://www.lrec-conf.org/proceedings/lrec2012/pdf/457_Paper.pdf",
pages = "2207--2213",
abstract = "In this paper, we present the architecture of a distributed resource repository developed for collecting training data for building customized statistical machine translation systems. The repository is designed for the cloud-based translation service integrated in the Let'sMT! platform which is about to be launched to the public. The system includes important features such as automatic import and alignment of textual documents in a variety of formats, a flexible database for meta-information using modern key-value stores and a grid-based backend for running off-line processes. The entire system is very modular and supports highly distributed setups to enable a maximum of flexibility and scalability. The system uses secure connections and includes an effective permission management to ensure data integrity. In this paper, we also take a closer look at the task of sentence alignment. The process of alignment is extremely important for the success of translation models trained on the platform. Alignment decisions significantly influence the quality of SMT engines.",
}
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%0 Conference Proceedings
%T A Distributed Resource Repository for Cloud-Based Machine Translation
%A Tiedemann, Jörg
%A Hansen, Dorte Haltrup
%A Offersgaard, Lene
%A Olsen, Sussi
%A Zumpe, Matthias
%Y Calzolari, Nicoletta
%Y Choukri, Khalid
%Y Declerck, Thierry
%Y Doğan, Mehmet Uğur
%Y Maegaard, Bente
%Y Mariani, Joseph
%Y Moreno, Asuncion
%Y Odijk, Jan
%Y Piperidis, Stelios
%S Proceedings of the Eighth International Conference on Language Resources and Evaluation (LREC’12)
%D 2012
%8 May
%I European Language Resources Association (ELRA)
%C Istanbul, Turkey
%F tiedemann-etal-2012-distributed
%X In this paper, we present the architecture of a distributed resource repository developed for collecting training data for building customized statistical machine translation systems. The repository is designed for the cloud-based translation service integrated in the Let’sMT! platform which is about to be launched to the public. The system includes important features such as automatic import and alignment of textual documents in a variety of formats, a flexible database for meta-information using modern key-value stores and a grid-based backend for running off-line processes. The entire system is very modular and supports highly distributed setups to enable a maximum of flexibility and scalability. The system uses secure connections and includes an effective permission management to ensure data integrity. In this paper, we also take a closer look at the task of sentence alignment. The process of alignment is extremely important for the success of translation models trained on the platform. Alignment decisions significantly influence the quality of SMT engines.
%U http://www.lrec-conf.org/proceedings/lrec2012/pdf/457_Paper.pdf
%P 2207-2213
Markdown (Informal)
[A Distributed Resource Repository for Cloud-Based Machine Translation](http://www.lrec-conf.org/proceedings/lrec2012/pdf/457_Paper.pdf) (Tiedemann et al., LREC 2012)
ACL
- Jörg Tiedemann, Dorte Haltrup Hansen, Lene Offersgaard, Sussi Olsen, and Matthias Zumpe. 2012. A Distributed Resource Repository for Cloud-Based Machine Translation. In Proceedings of the Eighth International Conference on Language Resources and Evaluation (LREC'12), pages 2207–2213, Istanbul, Turkey. European Language Resources Association (ELRA).