ITCH

May 30, 1998 | Projects

- PROJECT CLOSED

The project is concerned with new concepts for intelligent technologies supporting museum visits. Various areas of artificial intelligence are involved, including the production of dynamic presentations, group interaction support, user modelling, natural language processing, reasoning, tabletop collaborative systems, human-computer interaction.

MT Group at FBK Follow

#MachineTranslation Research Unit @FBK_research. #nlproc #deeplearning #ai

Avatar MT Group at FBK @fbk_mt ·

3 Jul

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

Zhihang Xie @FBKZhihangXie

🚀 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

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Avatar Fondazione Bruno Kessler - FBK @fbk_research ·

30 Jun

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/

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Avatar AILC_NLP @ailc_nlp ·

30 Jun

Emanuele Pianta Award for the Best Master’s Thesis in Computational Linguistics submitted at an Italian university and defended between August 1st 2024 and July 31st 2025
- Deadline: August 1st, 2025 (11:59 pm CEST)
- All details online: https://clic2025.unica.it/emanuele-pianta-award-for-the-best-masters-thesis/

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Avatar MT Group at FBK @fbk_mt ·

19 Jun

Our pick of the week by @DennisFucci: "Speech Representation Analysis Based on Inter- and Intra-Model Similarities" by Yassine El Kheir, Ahmed Ali, and Shammur Absar Chowdhury (ICASSP Workshops 2024)

#speech #speechtech

Dennis Fucci @DennisFucci

Findings from https://ieeexplore.ieee.org/document/10669908 show that speech SSL models converge on similar embedding spaces, but via different routes. While overall representations align, individual neurons learn distinct localized concepts.
Interesting read! @fbk_mt

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