In this talk, we cover the 2022 annual report on State of the Machine Translation, prepared together by Intento and e2f. The report analyses the performance of 20+ commercial MT engines across 9 industries (General, Colloquial, Education, Entertainment, Financial, Healthcare, Hospitality, IT, and Legal) and 10+ key language pairs. For the first time, this report is run using a unique dataset covering all language/domain combinations above, prepared by e2f. The presentation would focus on the process of data selection and preparation, the report methodology, principal scores to rely on when studying MT outcomes (COMET, BERTScore, PRISM, TER, and hLEPOR), and the main report outcomes (best performing MT engines for every language / domain combination). It includes a thorough comparison of the scores. It also covers language support, prices, and other features of the MT engines.

Managing large scale MT post-editing projects is a challenging endeavor. From securing linguists buy-in to ensuring consistency of the output, it is important to develop a set of specific processes and tools that facilitate this task. Drawing from years of experience in such projects, we will attempt here to describe the challenges associated to the management of such projects and to define best practices.