The TC-STAR project is envisaged as a long-term effort to advance research in all core technologies for Speech-to-Speech Translation (SST). SST technology is a combination of Automatic Speech Recognition (ASR), Spoken Language Translation (SLT) and Text to Speech (TTS) (speech synthesis). The objectives of the project are ambitious: making a breakthrough in SST that significantly reduces the gap between human and machine translation performance. The project targets a selection of unconstrained conversational speech domains—speeches and broadcast news—and three languages: European English, European Spanish, and Mandarin Chinese. Accurate translation of unrestricted speech is well beyond the capability of today’s state-of-the-art research systems. Therefore, advances are needed to improve the state-of the-art technologies for speech recognition and speech translation.
More great news! 🎉
Our paper “Echoes of Phonetics: Unveiling Relevant Acoustic Cues for ASR via Feature Attribution” was accepted at #Interspeech2025!
Interested in interpretability for speech models? Preprint coming soon!
✍🏼 @mgaido91, @negri_teo, M.Cettolo, @luisabentivogli
Our pick of the week by @BeatriceSavoldi: "Lost in Translation: Artificial Intelligence and the Demand for Foreign Language Skills" by @pmllanos and @carlbfrey (2025)
#AI #translation #MT
Super interesting preprint on the relation between MT improvements and the demand for foreign language skills #pickoftheweek @fbk_mt 📚https://www.oxfordmartin.ox.ac.uk/publications/lost-in-translation-artificial-intelligence-and-the-demand-for-foreign-language-skills
SHADES: a global dataset to uncover AI bias
Over 50 researchers, 16 languages, thousands of interactions analysed: the international SHADES project investigates how generative language models (LLM) reproduce and amplify cultural stereotypes
◾https://magazine.fbk.eu/en/news/shades-the-new-global-dataset-to-monitor-as-ai-reproduces-and-invents-cultural-stereotypes/
🎉 Excited to share our paper “Different Speech Translation Models Encode and Translate Speaker Gender Differently” was accepted at #ACL2025 (main)!
✍🏼 Big thanks to amazing co-authors: @mgaido91, @negri_teo, @luisabentivogli, @andre_t_martins, @peppeatta!
📄 Preprint out soon!