Feature Decay Algorithms for Neural Machine Translation
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http://hdl.handle.net/10045/76084
| Título: | Feature Decay Algorithms for Neural Machine Translation |
|---|---|
| Autor/es: | Poncelas, Alberto | Maillette de Buy Wenniger, Gideon | Way, Andy |
| Palabras clave: | Machine Translation |
| Área/s de conocimiento: | Lenguajes y Sistemas Informáticos |
| Fecha de publicación: | 2018 |
| Editor: | European Association for Machine Translation |
| Cita bibliográfica: | Poncelas, Alberto; Maillette de Buy Wenniger, Gideon; Way, Andy. “Feature Decay Algorithms for Neural Machine Translation”. In: Pérez-Ortiz, Juan Antonio, et al. (Eds.). Proceedings of the 21st Annual Conference of the European Association for Machine Translation: 28-30 May 2018, Universitat d'Alacant, Alacant, Spain, pp. 239-248 |
| Resumen: | Neural Machine Translation (NMT) systems require a lot of data to be competitive. For this reason, data selection techniques are used only for fine-tuning systems that have been trained with larger amounts of data. In this work we aim to use Feature Decay Algorithms (FDA) data selection techniques not only to fine-tune a system but also to build a complete system with less data. Our findings reveal that it is possible to find a subset of sentence pairs, that outperforms by 1.11 BLEU points the full training corpus, when used for training a German-English NMT system. |
| Patrocinador/es: | This research has been supported by the ADAPT Centre for Digital Content Technology which is funded under the SFI Research Centres Programme (Grant 13/RC/2106) and is co-funded under the European Regional Development Fund. This work has also received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No 713567. |
| URI: | http://hdl.handle.net/10045/76084 |
| ISBN: | 978-84-09-01901-4 |
| Idioma: | eng |
| Tipo: | info:eu-repo/semantics/conferenceObject |
| Derechos: | © 2018 The authors. This article is licensed under a Creative Commons 3.0 licence, no derivative works, attribution, CC-BY-ND. |
| Revisión científica: | si |
| Versión del editor: | http://eamt2018.dlsi.ua.es/proceedings-eamt2018.pdf |
| Aparece en las colecciones: | Investigaciones financiadas por la UE EAMT2018 - Proceedings |
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| Archivo | Descripción | Tamaño | Formato | |
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 EAMT2018-Proceedings_26.pdf | 1,61 MB | Adobe PDF | Abrir Vista previa | |
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