Toward a full-scale neural machine translation in production: the Booking.com use case
This work addresses the practical deployment of NMT for a specific company's needs, but it is incremental as it applies existing methods to new data without introducing novel techniques.
The paper tackles the challenge of deploying neural machine translation (NMT) in a large-scale e-commerce setting, specifically for travel domain content at Booking.com, and reports findings on optimization, handling real-world content, and evaluation.
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.