Implementing a neural machine translation engine for mobile devices: the Lingvanex use case
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Título: | Implementing a neural machine translation engine for mobile devices: the Lingvanex use case |
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Autor/es: | Parcheta, Zuzanna | Sanchis-Trilles, Germán | Rudak, Aliaksei | Bratchenia, Siarhei |
Palabras clave: | Machine Translation |
Área/s de conocimiento: | Lenguajes y Sistemas Informáticos |
Fecha de publicación: | 2018 |
Editor: | European Association for Machine Translation |
Cita bibliográfica: | Parcheta, Zuzanna, et al. “Implementing a neural machine translation engine for mobile devices: the Lingvanex use case”. 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. 297-302 |
Resumen: | In this paper, we present the challenge entailed by implementing a mobile version of a neural machine translation system, where the goal is to maximise translation quality while minimising model size. We explain the whole process of implementing the translation engine on an English–Spanish example and we describe all the difficulties found and the solutions implemented. The main techniques used in this work are data selection by means of Infrequent n-gram Recovery, appending a special word at the end of each sentence, and generating additional samples without the final punctuation marks. The last two techniques were devised with the purpose of achieving a translation model that generates sentences without the final full stop, or other punctuation marks. Also, in this work, the Infrequent n-gram Recovery was used for the first time to create a new corpus, and not enlarge the in-domain dataset. Finally, we get a small size model with quality good enough to serve for daily use. |
Patrocinador/es: | Work partially supported by MINECO under grant DI-15-08169 and by Sciling under its R+D programme. |
URI: | http://hdl.handle.net/10045/76108 |
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: | EAMT2018 - Proceedings |
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