English-Basque Statistical and Neural Machine Translation

被引：0

作者：

Unanue, Inigo Jauregi ^{[1
,2
]}

Garmendia Arratibel, Lierni

Borzeshi, Ehsan Zare ^{[2
]}

Piccardi, Massimo ^{[1
]}

机构：

[1] Univ Technol Sydney UTS, Sydney, NSW, Australia

[2] Capital Markets Cooperat Res Ctr CMCRC, Sydney, NSW, Australia

来源：

PROCEEDINGS OF THE ELEVENTH INTERNATIONAL CONFERENCE ON LANGUAGE RESOURCES AND EVALUATION (LREC 2018) | 2018年

关键词：

Neural Machine Translation; Statistical Machine Translation; English-Basque; Basque;

D O I：

暂无

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

Neural Machine Translation (NMT) has attracted increasing attention in the recent years. However, it tends to require very large training corpora which could prove problematic for languages with low resources. For this reason, Statistical Machine Translation (SMT) continues to be a popular approach for low-resource language pairs. In this work, we address English-Basque translation and compare the performance of three contemporary statistical and neural machine translation systems: OpenNMT, Moses SMT and Google Translate. For evaluation, we employ an open-domain and an IT-domain corpora from the WMT16 resources for machine translation. In addition, we release a small dataset (Berriak) of 500 highly-accurate English-Basque translations of complex sentences useful for a thorough testing of the translation systems.

引用

页码：880 / 885

页数：6

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