A Distributed Resource Repository for Cloud-Based Machine Translation

Jörg Tiedemann, Dorte Haltrup Hansen, Lene Offersgaard, Sussi Olsen, Matthias Zumpe

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.

Original languageEnglish
Title of host publicationProceedings of the Eighth International Conference on Language Resources and Evaluation (LREC'12)
Place of PublicationIstanbul,Tyrkiet
PublisherEuropean Language Resources Association
Publication date2012
Pages2207-2213
ISBN (Print)978-2-9517408-7-7
Publication statusPublished - 2012
EventInternational Conference on Language Resources and Evaluation - Istanbul, Turkey
Duration: 23 May 201225 May 2012
Conference number: 8

Conference

ConferenceInternational Conference on Language Resources and Evaluation
Number8
Country/TerritoryTurkey
CityIstanbul
Period23/05/201225/05/2012

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