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.
A special evening in Rome to talk about Physical AI and Europe’s role in shaping this new frontier.
Partners from across Europe came together to present the DVPS project, and connect with key people from public institutions, embassies, industries, national & international media.
Thrilled to be part of this amazing project and team!
🚀 DVPS has launched at Translated's HQ!
70 researchers from 20 institutions across 9 countries unite to build next-gen multimodal foundation models that learn from real-world interaction.
A new European AI journey begins.
#DVPS #PhysicalAI #HorizonEurope #MultimodalAI
Our pick of the week by @FBKZhihangXie: "PHRASED: Phrase Dictionary Biasing for Speech Translation" by Peidong Wang, Jian Xue, Rui Zhao, @ChenJunkun, Aswin Shanmugam Subramanian, and Jinyu Li (2025).
#Speech #SpeechAI #Translation #ST #SpeechTranslation
🚀 Boost rare-phrase translation in speech! Uses **bilingual dictionaries** to dynamically bias outputs.
✅ **+21%** recall in streaming ST
✅ **+85%** in multimodal LLMs
🔗: http://arxiv.org/abs/2506.09175
FAMA è il primo foundation model vocale open-science per ita e eng, sviluppato da FBK. Riconosce e traduce la voce usando solo dati e strumenti pubblici: oltre 150.000 ore di audio open, codice e processi completamente accessibili.
@fbk_stek @fbk_mt
https://magazine.fbk.eu/it/news/la-prima-famiglia-di-modelli-open-science-per-il-riconoscimento-vocale-e-la-traduzione-del-parlato/