Slator 2021 Language Industry Market Report
80-pages. Market Size by Vertical, Geo, Intention. Expert-in-Loop Model. M&A. Frontier Tech. Hybrid Future. Outlook 2021-2025.
LTs and AI have had a “transformative effect” on language services, the paper said, achieved by enabling greater automation of tasks. Although productivity tools (CAT) have long been the de facto standard and are deeply ingrained in language production, “the future smarter CAT environment is yet to be developed,” according to the EU host paper. Tools can be lacking in user friendlessness (UX) and many do not integrate sufficiently with terminology, MT, workflow, and CMS systems.
“The future smarter CAT environment is yet to be developed.”
Machine translation, and NMT in particular, has become “an integral part of a linguist’s toolbox” in recent years, according to the paper. The paradigm shift achieved by NMT is a result of its ability to produce better quality and more fluent translation output.
Slator 2021 Data-for-AI Market Report
44-pages on how LSPs enter and scale in AI Data-as-a-service. Market overview, AI use cases, platforms, case studies, sales insights.
Right now, “most EU translation services have integrated eTranslation in their pre-processing arrangements and provide NMT output to their linguists.” eTranslation, the EU’s MT service, is based on more than one billion sentences from the EU’s Euramis translation memories, which exist in all of the EU’s 24 official languages.
“Most EU translation services have integrated eTranslation in their pre-processing arrangements and provide NMT output to their linguists.”
Outside of translation, the application of LTs and AI within conference interpretation is still limited, however, and restricted to assisting with discrete tasks such as meeting preparation and key term prompts.
The paper also highlights the use of LTs and AI in the areas of terminology management, speech recognition, and conference management; for instance, in helping meet the challenge of programming “up to 1,000 interpreters’ assignments for an average of 40 meetings a day.”
There are several hurdles that will need to be overcome for LTs and AI to become even more useful in language production, the EU paper stated. Among them are the management challenge of helping alleviate fear and uncertainty around what these technologies mean for jobs; the current absence of well curated data for training; and the notion that a linguist’s translation and language skills could possibly degrade once they are no longer responsible for the production of a translation.
Along with the increased use of language technologies and AI, there is a clear benefit for language professionals, since, as the paper posits, “LTs and AI ideally take over the mundane part of language professionals’ work, making it possible for them to spend more time on the creative aspects.”
“LTs and AI ideally take over the mundane part of language professionals’ work.”
The EU, for one, is driving a number of operational developments to adapt to the shifting landscape. They created the role of Language Technology Coordinator in 2018 across all 24 EU languages, and have also set up an AI incubator, a CAT Network, and a CAT Helpline, which comprises a “group of translators and translation assistants who voluntarily provide peer-to-peer support across all language units, in collaboration with the IT Helpline and using the IT department’s issue tracking system to manage support requests.”
The paper underscored the EU’s commitment to LTs and AI, and goes as far as calling them “the third revolution as far as human language is concerned, after the creation of the alphabet and writing and then the invention of printing.”
