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.
Our pick of the week by @lina97337786: "Towards a Deep Understanding of Multilingual End-to-End Speech Translation" by @hrsun42, @YikunLei et al., Findings EMNLP 2023.
#NLP #NLProc #EMNLP2023 #speech #translation #multilingual
🎉 AI-GAP workshop wrapped up yesterday!
Huge thanks to the participants, speakers, and organizers -- we were very happy, as you can see :)
@donatellado @BeatriceSavoldi @costanzalfieri @ECappu Clara Punzi & Laura State
🎊 I'm very happy to share that the paper "Direct Speech Translation for Automatic Subtitling" accepted by the #TACL journal is now published and available at:
#NLP #NLProc #subtitling #speech #translation
📢 @BeatriceSavoldi from @fbk_mt (@FBK_research) is co-organizing the AI GAP Workshop, held in collaboration with @Unipisa, @univaq, and @scuolanormale!
👉 Check the website for more information:
#AI #ArtificialIntelligence #AlgorithmicBias