Toward a full-scale neural machine translation in production: the Booking.com use case

Autor:	Levin, Pavel, Dhanuka, Nishikant, Khalil, Talaat, Kovalev, Fedor, Khalilov, Maxim
Rok vydání:	2017
Předmět:	Computer Science - Computation and Language
Druh dokumentu:	Working Paper
Popis:	While some remarkable progress has been made in neural machine translation (NMT) research, there have not been many reports on its development and evaluation in practice. This paper tries to fill this gap by presenting some of our findings from building an in-house travel domain NMT system in a large scale E-commerce setting. The three major topics that we cover are optimization and training (including different optimization strategies and corpus sizes), handling real-world content and evaluating results. Comment: 11 pages, 4 figures, presented at MT Summit XVI, Commercial MT Users and Translators Track
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/1709.05820 Zobrazit plný text záznamu View this record from Arxiv