Machine translation is the process of using an engine to automatically translate human input text from one language to another.
In recent years, machine translation has received more attention, as companies have started using it in their own operations. The benefits for companies are realised in the form of operational efficiency, time used on translating texts and translation costs. Machine translation is based on computational linguistics, where the machine translates source text into the desired target language. The size of the market is predicted to grow from 800 million USD in 2021 to 7.5 billion USD by 2030, with an annual growth rate of 30% from 2022 to 2030, according to Global Market Insight. Popularity of the cloud-based application, and customer-driven company operations have been recognised as the key driver for this growth.
The European Commission has created the eTranslation service for public administration and small and medium-sized enterprises (SMEs). The eTranslation service is intended to provide a quick, raw machine translation from and into any European language, including Icelandic and Norwegian, free of charge.
Also, several institutions have started their own machine translation projects, aiming to create machine translation engines or services to reduce existing language barriers. For example, the University of Tartu partnered with Baltic language technology and localisation company Tilde for an open-source machine translator engine development. The aim is to provide an engine that can translate Estonian to and from English, Russian and German. The development also aims at advancing the state of machine translation in Estonia and testing new methods for translating.
Another interesting initiative for cross-border data exchange is AuroraAI, a Finnish national artificial intelligence programme started in 2020. The goal of AuroraAI is to connect public sector organisations through the AuroraAI network. The purpose is to create technical conditions that will enable information exchange and interoperability between different services and platforms. This could be a potentially interesting initiative for cross-border data exchange as well.
This report takes an overview on available machine translation engines and services. The report first summarises machine translation methods and their key concepts, then takes a quick overview on the machine translation service market, and finally summarises some of the benefits and potential challenges of those services from the perspective of the Cross-Border Data Exchange (CBDE) Project.