1 code implementation • LREC 2022 • Jaume Zaragoza-Bernabeu, Gema Ramírez-Sánchez, Marta Bañón, Sergio Ortiz Rojas
This paper describes the experiments carried out during the development of the latest version of Bicleaner, named Bicleaner AI, a tool that aims at detecting noisy sentences in parallel corpora.
1 code implementation • EAMT 2020 • Gema Ramírez-Sánchez, Jaume Zaragoza-Bernabeu, Marta Bañón, Sergio Ortiz Rojas
This paper shows the utility of two open-source tools designed for parallel data cleaning: Bifixer and Bicleaner.
no code implementations • HumEval (ACL) 2022 • Gema Ramírez-Sánchez, Marta Bañón, Jaume Zaragoza-Bernabeu, Sergio Ortiz Rojas
Quality assessment has been an ongoing activity of the series of ParaCrawl efforts to crawl massive amounts of parallel data from multilingual websites for 29 languages.
no code implementations • EAMT 2022 • Marta Bañón, Miquel Esplà-Gomis, Mikel L. Forcada, Cristian García-Romero, Taja Kuzman, Nikola Ljubešić, Rik van Noord, Leopoldo Pla Sempere, Gema Ramírez-Sánchez, Peter Rupnik, Vít Suchomel, Antonio Toral, Tobias van der Werff, Jaume Zaragoza
We introduce the project “MaCoCu: Massive collection and curation of monolingual and bilingual data: focus on under-resourced languages”, funded by the Connecting Europe Facility, which is aimed at building monolingual and parallel corpora for under-resourced European languages.
no code implementations • 12 Apr 2024 • Marta Bañón, Jaume Zaragoza-Bernabeu, Gema Ramírez-Sánchez, Sergio Ortiz-Rojas
Language identification is a crucial component in the automated production of language resources, particularly in multilingual and big data contexts.
no code implementations • 20 Mar 2024 • Ona de Gibert, Graeme Nail, Nikolay Arefyev, Marta Bañón, Jelmer Van der Linde, Shaoxiong Ji, Jaume Zaragoza-Bernabeu, Mikko Aulamo, Gema Ramírez-Sánchez, Andrey Kutuzov, Sampo Pyysalo, Stephan Oepen, Jörg Tiedemann
We present the HPLT (High Performance Language Technologies) language resources, a new massive multilingual dataset including both monolingual and bilingual corpora extracted from CommonCrawl and previously unused web crawls from the Internet Archive.