collaborators

6 papers

cs.CL2026

Ouvia: A User-centered Framework for Measuring Usability of Speech Translation in Real-World Communication Scenarios

Giuseppe Attanasio, Beatrice Savoldi, Daniel Chechelnitsky +4

Speech translation (ST) is increasingly adopted in user applications, yet its evaluation largely focuses on decontextualized testbeds and holistic quality, rather than end users' c…

cs.CL2026

SEQUOR: A Multi-Turn Benchmark for Realistic Constraint Following

Beatriz Canaverde, Duarte M. Alves, José Pombal +2

In a conversation, a helpful assistant must reliably follow user directives, even as they refine, modify, or contradict earlier requests. Yet most instruction-following benchmarks…

cs.CL2025

Instituto de Telecomunicações at IWSLT 2025: Aligning Small-Scale Speech and Language Models for Speech-to-Text Learning

Giuseppe Attanasio, Sonal Sannigrahi, Ben Peters +1

This paper presents the IT-IST submission to the IWSLT 2025 Shared Task on Instruction Following Speech Processing. We submit results for the Short Track, i.e., speech recognition,…

cs.CV2025

Movie Facts and Fibs (MF): A Benchmark for Long Movie Understanding

Emmanouil Zaranis, António Farinhas, Saul Santos +28

Despite recent progress in vision-language models (VLMs), holistic understanding of long-form video content remains a significant challenge, partly due to limitations in current be…

cs.CL2025

Different Speech Translation Models Encode and Translate Speaker Gender Differently

Dennis Fucci, Marco Gaido, Matteo Negri +3

Recent studies on interpreting the hidden states of speech models have shown their ability to capture speaker-specific features, including gender. Does this finding also hold for s…

cs.CL2025

Watching the Watchers: Exposing Gender Disparities in Machine Translation Quality Estimation

Emmanouil Zaranis, Giuseppe Attanasio, Sweta Agrawal +1

Quality estimation (QE)-the automatic assessment of translation quality-has recently become crucial across several stages of the translation pipeline, from data curation to trainin…