MateCat worked at a new frontier of Computer Assisted Translation (CAT) technology, that is, how to effectively and ergonomically integrate Machine Translation (MT) within the human translation workflow. At a time in which MT was mainly trained with the objective of creating the most comprehensible output, MateCat targeted the development of MT technology aimed at minimizing the translator’s post-edit effort. To this end, MateCat developed an enhanced web-based CAT tool offering new MT capabilities, such as automatic adaption to the translated content, online learning from user corrections, and automatic quality estimation.
🎙️ Two people. Two languages. One conversation!
No delays. No switching languages. No one is left out.
This is what we are building.
#SpeechAI #MultilingualAI #HorizonEurope
Four years ago, NLLB set a milestone with MT for 200 languages. Today we present OMT: a family of models that extend support to 1600 languages while delivering competitive results in high/mid-resource language, with our 1B-8B models matching frontier and open 70B LLMs.
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📢I'm organizing a BoF session at #EACL2026 called Tokenization & Beyond, aiming to gather researchers exploring tokenization and alternatives such as byte-level and pixel-based approaches. Sign up using the form if you're interested! #NLProc @eaclmeeting