There are two interleaved high-level goals for the EXCITEMENT project. The first is to set up, for the first time, a generic architecture and a comprehensive implementation for a multilingual textual inference platform and to make it available to the scientific and technological communities. The second goal of the project is to develop a new generation of inference-based industrial text exploration applications for customer interactions, which enables businesses to better analyze and make sense of their diverse and often unpredicted client content. These goals were be achieved for three languages, i.e. English, German and Italian, and for three customer interaction channels, i.e. speech (transcriptions), email and social media.
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!
🎉 Excited to share that our @sarapapi has won the 2024 Best PhD Award from the Information and Engineering Doctoral School at @UniTrento_DISI for her thesis “Direct Speech Translation in Constrained Contexts: The Simultaneous and Subtitling Scenarios.”
#nlproc @FBK_research
🎉 Excited to share that our @sarapapi has won the 2024 Best PhD Award from the Information and Engineering Doctoral School at @UniTrento_DISI for her thesis “Direct Speech Translation in Constrained Contexts: The Simultaneous and Subtitling Scenarios.”
#nlproc @FBK_research