Automating Machine Translation Quality Estimation Gains Traction
Interest in automating machine translation quality estimation increases with the prevalence of large language models, but still has some way to go to be deployed at scale.
Interest in automating machine translation quality estimation increases with the prevalence of large language models, but still has some way to go to be deployed at scale.
The Slator Pro Guide: Translation AI is a vital and concise guide to applying large language models (LLMs) in translation workflows, featuring 10 practical use cases.
Georg Ell on his first 15 months leading Phrase and how they are prioritizing capabilities such as quality estimation, no-code workflow automation, TMS, and dynamic MT engine routing.
60-page report on interaction between human experts and AI in translation production; includes AI-enabled workflows, adoption rates, postediting, pricing models.
Amazon Prime Video researchers have developed a new quality estimation system for subtitle translations, which tells you when post-editing or rewrites are needed.
Memsource has released a second AI-powered feature, Machine Translation Quality
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