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Machine-readable Finnish-Livvi bilingual translation dictionary ...
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Machine-readable Finnish-Karelian bilingual translation dictionary ...
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Machine-readable Finnish-Karelian bilingual translation dictionary ...
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Machine-readable Northern Karelian Proper-Livvi bilingual translation dictionary ...
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Machine-readable Finnish-Livvi bilingual translation dictionary ...
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Machine-readable Northern Karelian Proper-Livvi bilingual translation dictionary ...
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Česílko 2.0 Shallow Transfer RBMT framework (opensource version)
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Integrating Rules and Dictionaries from Shallow-Transfer Machine Translation into Phrase-Based Statistical Machine Translation
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RuLearn: an Open-source Toolkit for the Automatic Inference of Shallow-transfer Rules for Machine Translation
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A Fast Implementation of Rules Based Machine Translation Systems for Similar Natural Languages
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In: http://www.informatica.si/PDF/37-4/31_Vicic - A Fast Implementation of Rules Based Machine Translation Systems for Similar Natural Languages.pdf (2013)
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An open-source toolkit for integrating shallow-transfer rules into phrase-based statistical machine translation
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The Universitat d’Alacant hybrid machine translation system for WMT 2011
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| 13 |
Integrating shallow-transfer rules into phrase-based statistical machine translation
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An open-source shallow-transfer machine translation toolbox: consequences of its release and availability
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An open-source shallow-transfer machine translation engine for the Romance languages of Spain
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Corbí Bellot, Antonio Miguel; Forcada, Mikel L.; Ortiz Rojas, Sergio; Pérez-Ortiz, Juan Antonio; Ramírez Sánchez, Gema; Sánchez-Martínez, Felipe; Alegría Loinaz, Iñaki; Mayor Martínez, Aingeru; Sarasola Gabiola, Kepa. - : European Association for Machine Translation, 2005
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Abstract:
We present the current status of development of an open-source shallow-transfer machine translation engine for the Romance languages of Spain (the main ones being Spanish, Catalan and Galician) as part of a larger government-funded project which includes non-Romance languages such as Basque and involving both universities and linguistic technology companies. The machine translation architecture uses finite-state transducers for lexical processing, hidden Markov models for part-of-speech tagging, and finite-state based chunking for structural transfer, and is largely based upon that of systems already developed by the Transducens group at the Universitat d'Alacant, such as interNOSTRUM (Spanish—Catalan) and Traductor Universia (Spanish—Portuguese). The possible scope of the project, however, is wider, since it will be possible to use the resulting machine translation system with new pairs of languages; to that end, the project also aims at proposing standard formats to encode the linguistic data needed. This paper briefly describes the machine translation engine, the formats it uses for linguistic data, and the compilers that convert these data into an efficient format used by the engine. ; Work funded by projects FIT-340101-2004-3 (Spanish Ministry of Industry, Commerce and Tourism) and TIC2003-08681-C02-01 (Spanish Ministry of Science and Technology). Felipe Sánchez-Martínez is supported by the Spanish Ministry of Science and Education and the European Social Fund through grant BES-2004-4711.
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Keyword:
Lenguajes y Sistemas Informáticos; Machine translation; Romance languages; Shallow-transfer
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URL: http://hdl.handle.net/10045/27525
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