Apertium: a free/open-source platform for rule-based machine translation
By Mikel L. Forcada, Mireia Ginestí-Rosell, Jacob Nordfalk, Jimmy O'Regan, Sergio Ortiz Rojas, Juan Antonio Pérez-Ortiz, Felipe Sánchez-Martínez, Gema Ramírez-Sánchez, Francis M. Tyers. Machine Translation, 2011
419 citations recorded by the source corpus.
Subfields: Artificial Intelligence
View Paper: https://www.semanticscholar.org/paper/973e9ab3be7978850f79cc83497259f3306d8e3d
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Citations in the corpus
- Translation Task : Two-step Data Selection and RBMT-Style Synthetic Rules (2014, background): “In summary, rules are obtained from a set of bilingual phrases extracted from the parallel corpus after its morphological analysis and part-of-speech disambiguation with the tools in the Apertium rulebased MT platform (Forcada et al., 2011).”
- The TALP-UPC Machine Translation Systems for WMT19 News Translation Task: Pivoting Techniques for Low Resource MT (2019, methodology): “The Apertium Rule-based Machine Translation (RBMT) system (Forcada et al., 2011) offers a generic platform to implement transfer-based rule systems for translation.”
- Why Catalan-Spanish Neural Machine Translation? Analysis, comparison and combination with standard Rule and Phrase-based technologies (2017, methodology): “Rule-based We use the Apertium rule-based system (Forcada et al., 2011).”
- GF Wide-coverage English-Finnish MT system for WMT 2015 (2015, methodology): “It is inspired by Apertium(Forcada et al., 2011), which is a rule-based system operating only using chunks rather than deep syntactic analyses.”
- The UA-Prompsit hybrid machine translation system for the 2014 Workshop on Statistical Machine Translation (2014, methodology): “…2011b) which consisted of enriching the phrase table of a PBSMT system with phrase pairs generated using the dictionaries and rules in the Apertium (Forcada et al., 2011) Spanish–English RBMT system; our approach was one of the winners1 (together with two online SMT systems that were not…”
- Adaptation of machine translation for multilingual information retrieval in the medical domain (2014, background): “…Union law [13], the News Commentary corpus of news analysis from the Project Syndicate [14], and the OJEU corpus with texts from the Official Journal of the European Union including legislation documents , information notices, and public procurements, made available by the Apertium project [60].”