Architecture of a Scalable, Secure and Resilient Translation Platform for Multilingual News Media

Susie Coleman (1) , Andrew Secker (1) , Rachel Bawden (2) , Barry Haddow (2) , Alexandra Birch (2)

1 BBC - British Broadcasting Corporation (Entreprise)
2 School of Informatics [Edimbourg]

This paper presents an example architecture for a scalable, secure and resilient Machine Translation (MT) platform, using components available via Amazon Web Services (AWS). It is increasingly common for a single news organisation to publish and monitor news sources in multiple languages. A growth in news sources makes this increasingly challenging and time-consuming but MT can help automate some aspects of this process. Building a translation service provides a single integration point for news room tools that use translation technology allowing MT models to be integrated into a system once, rather than each time the translation technology is needed. By using a range of services provided by AWS, it is possible to architect a platform where multiple pre-existing technologies are combined to build a solution, as opposed to developing software from scratch for deployment on a single virtual machine. This increases the speed at which a platform can be developed and allows the use of well-maintained services. However, a single service also provides challenges. It is key to consider how the platform will scale when handling many users and how to ensure the platform is resilient.

Mots clés: Machine translation; AWS; Platform; News media

Domaines: Informatique et langage [cs.CL]

Susie Coleman, Andrew Secker, Rachel Bawden, Barry Haddow, Alexandra Birch. Architecture of a Scalable, Secure and Resilient Translation Platform for Multilingual News Media. 1st International Workshop on Language Technology Platforms, 2020, Marseille, France. pp.16-21. ⟨hal-02900633⟩