n EY ron: Implementation and Deployment of an MT System for a Large Audit & Consulting Corporation (2022)

Abstract: This paper reports on the implementation and deployment of an MT system in the Polish branch of EY Global Limited. The system supports standard CAT and MT functionalities such as translation memory fuzzy search, document translation and post-editing, and meets less common, customer-specific expectations. The deployment began in August 2018 with a Proof of Concept, and ended with the signing of the Final Version acceptance certificate in October 2021. We present the challenges that were faced during the deployment, particularly in relation to the security check and installation processes in the production environment.

## system components the architecture of the system consists of the following components: ## future plans plans for the future include technical improvements to the existing solution, as well as the introduction of new features. small improvements may include replacing hunalign @xcite with vecalign @xcite in the bilingual corpus extraction process described in section 4.1. we expect that the translation quality of nmt models will improve as a result of better corpus alignment. to further improve the quality of the nmt models, we intend to use existing monolingual customer documents. we plan to apply the backtranslation @xcite technique iteratively @xcite to increase the quality of our models. as new terminology emerges, the user expects mt systems to quickly adapt to them. in most cases, data that would cover the new terminology do not yet exist. to solve this problem, we intend to use techniques for forced terminology translation @xcite to ensure that specific terminology is translated according to the needs of the user. additionally, providing a glossary with specific in-domain terminology would ensure the consistent translation of such terminology when different sentences are translated. to date, we have relied on the bleu @xcite metric for the evaluation of trained nmt models. to follow current state-of-the-art solutions in mt evaluation, we plan to use the mt telescope @xcite to evaluate our models with the comet @xcite metric and perform a fine-grained error analysis. business documents often have a complex layout structure, whereas current nmt models operate only on sentence-level textual semantics. we want to explore the idea of integrating nmt with computer vision to create an end-to-end model which would learn visual features, layout information and textual semantics to produce documentlevel translations better than the current state-ofthe-art methods. such a model would be able to simplify the process of text extraction, sentence segmentation and document reconstruction, as it would take all document information as an input. to this end, we plan to base our model on the tilt @xcite architecture. this was created for the question answering task, but we believe that it could be modified for nmt. ## conclusions this paper has presented the deployment of an english-polish translation system at the polish branch of ey global limited. the system supports standard cat and mt functionalities such as translation memory fuzzy search, document translation and post-editing, and meets less frequent expectations such as single sign-on login and calculation of the cost of human translation for a given document. the paper has presented the challenges that were faced during the deployment, particularly adherence to security expectations and installation in the production environment. ultimately, the deployment took over three years. meanwhile, new technologies have been developed in the field of machine translation. once the security issues have been overcome, we hope to be able to update the system with emerging technologies, constantly improving its performance.