@inproceedings{etchegoyhen-etal-2018-neural,
title = "Neural Machine Translation of {B}asque",
author = "Etchegoyhen, Thierry and
Mart{\'\i}nez Garcia, Eva and
Azpeitia, Andoni and
Labaka, Gorka and
Alegria, I{\~n}aki and
Cortes Etxabe, Itziar and
Jauregi Carrera, Amaia and
Ellakuria Santos, Igor and
Martin, Maite and
Calonge, Eusebi",
editor = "P{\'e}rez-Ortiz, Juan Antonio and
S{\'a}nchez-Mart{\'\i}nez, Felipe and
Espl{\`a}-Gomis, Miquel and
Popovi{\'c}, Maja and
Rico, Celia and
Martins, Andr{\'e} and
Van den Bogaert, Joachim and
Forcada, Mikel L.",
booktitle = "Proceedings of the 21st Annual Conference of the European Association for Machine Translation",
month = may,
year = "2018",
address = "Alicante, Spain",
url = "https://aclanthology.org/2018.eamt-main.14",
pages = "159--168",
abstract = "We describe the first experimental results in neural machine translation for Basque. As a synthetic language featuring agglutinative morphology, an extended case system, complex verbal morphology and relatively free word order, Basque presents a large number of challenging characteristics for machine translation in general, and for data-driven approaches such as attentionbased encoder-decoder models in particular. We present our results on a large range of experiments in Basque-Spanish translation, comparing several neural machine translation system variants with both rule-based and statistical machine translation systems. We demonstrate that significant gains can be obtained with a neural network approach for this challenging language pair, and describe optimal configurations in terms of word segmentation and decoding parameters, measured against test sets that feature multiple references to account for word order variability.",
}
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%0 Conference Proceedings
%T Neural Machine Translation of Basque
%A Etchegoyhen, Thierry
%A Martínez Garcia, Eva
%A Azpeitia, Andoni
%A Labaka, Gorka
%A Alegria, Iñaki
%A Cortes Etxabe, Itziar
%A Jauregi Carrera, Amaia
%A Ellakuria Santos, Igor
%A Martin, Maite
%A Calonge, Eusebi
%Y Pérez-Ortiz, Juan Antonio
%Y Sánchez-Martínez, Felipe
%Y Esplà-Gomis, Miquel
%Y Popović, Maja
%Y Rico, Celia
%Y Martins, André
%Y Van den Bogaert, Joachim
%Y Forcada, Mikel L.
%S Proceedings of the 21st Annual Conference of the European Association for Machine Translation
%D 2018
%8 May
%C Alicante, Spain
%F etchegoyhen-etal-2018-neural
%X We describe the first experimental results in neural machine translation for Basque. As a synthetic language featuring agglutinative morphology, an extended case system, complex verbal morphology and relatively free word order, Basque presents a large number of challenging characteristics for machine translation in general, and for data-driven approaches such as attentionbased encoder-decoder models in particular. We present our results on a large range of experiments in Basque-Spanish translation, comparing several neural machine translation system variants with both rule-based and statistical machine translation systems. We demonstrate that significant gains can be obtained with a neural network approach for this challenging language pair, and describe optimal configurations in terms of word segmentation and decoding parameters, measured against test sets that feature multiple references to account for word order variability.
%U https://aclanthology.org/2018.eamt-main.14
%P 159-168
Markdown (Informal)
[Neural Machine Translation of Basque](https://aclanthology.org/2018.eamt-main.14) (Etchegoyhen et al., EAMT 2018)
ACL
- Thierry Etchegoyhen, Eva Martínez Garcia, Andoni Azpeitia, Gorka Labaka, Iñaki Alegria, Itziar Cortes Etxabe, Amaia Jauregi Carrera, Igor Ellakuria Santos, Maite Martin, and Eusebi Calonge. 2018. Neural Machine Translation of Basque. In Proceedings of the 21st Annual Conference of the European Association for Machine Translation, pages 159–168, Alicante, Spain.