Parallel text is the fuel that drives modern machine translation systems. The Web is a
comprehensive source of preexisting parallel text, but crawling the entire web is impossible …

Recent machine translation algorithms mainly rely on parallel corpora. However, since the
availability of parallel corpora remains limited, only some resource-rich language pairs can …

We report on methods to create the largest publicly available parallel corpora by crawling
the web, using open source software. We empirically compare alternative methods and …

We describe two projects funded by the Connecting Europe Facility, Provision of Web-Scale
Parallel Corpora for Official European Languages (2016-EU-IA-0114, completed) and …

Most current machine translation models are mainly trained with parallel corpora, and their
translation accuracy largely depends on the quality and quantity of the corpora. Although …

Cross-lingual document alignment aims to identify pairs of documents in two distinct
languages that are of comparable content or translations of each other. In this paper, we …

Machine translation is highly sensitive to the size and quality of the training data, which has
led to an increasing interest in collecting and filtering large parallel corpora. In this paper, we …

Parallel corpora are a valuable resource for machine translation, but at present their
availability and utility is limited by genre-and domain-specificity, licensing restrictions, and …

This paper shows the utility of two open-source tools designed for parallel data cleaning:
Bifixer and Bicleaner. Already used to clean highly noisy parallel content from crawled …

Despite the fact that document-level machine translation has inherent advantages over
sentence-level machine translation due to additional information available to a model from …