activity
20222025
most citedFindings of the IWSLT 2024 Evaluation Campaign

5 citations · 7 across the 12 of their papers we have counts for

collaborators

15 papers

cs.CL2025

Challenging the Abilities of Large Language Models in Italian: a Community Initiative

Malvina Nissim, Danilo Croce, Viviana Patti +78

The rapid progress of Large Language Models (LLMs) has transformed natural language processing and broadened its impact across research and society. Yet, systematic evaluation of t…

cs.CL2025

Simulstream: Open-Source Toolkit for Evaluation and Demonstration of Streaming Speech-to-Text Translation Systems

Marco Gaido, Sara Papi, Mauro Cettolo +2

Streaming Speech-to-Text Translation (StreamST) requires producing translations concurrently with incoming speech under strict latency constraints, demanding models that balance lo…

cs.CL2025

How to Evaluate Speech Translation with Source-Aware Neural MT Metrics

Mauro Cettolo, Marco Gaido, Matteo Negri +2

Automatic evaluation of ST systems is typically performed by comparing translation hypotheses with one or more reference translations. While effective to some extent, this approach…

cs.CL2025

Echoes of Phonetics: Unveiling Relevant Acoustic Cues for ASR via Feature Attribution

Dennis Fucci, Marco Gaido, Matteo Negri +2

Despite significant advances in ASR, the specific acoustic cues models rely on remain unclear. Prior studies have examined such cues on a limited set of phonemes and outdated model…

cs.CL2025

FAMA: The First Large-Scale Open-Science Speech Foundation Model for English and Italian

Sara Papi, Marco Gaido, Luisa Bentivogli +6

The development of speech foundation models (SFMs) like Whisper and SeamlessM4T has significantly advanced the field of speech processing. However, their closed nature--with inacce…

cs.CL2025

The Warmup Dilemma: How Learning Rate Strategies Impact Speech-to-Text Model Convergence

Marco Gaido, Sara Papi, Luisa Bentivogli +6

Training large-scale models presents challenges not only in terms of resource requirements but also in terms of their convergence. For this reason, the learning rate (LR) is often…

cs.CL2024★ 5 cited

Findings of the IWSLT 2024 Evaluation Campaign

Ibrahim Said Ahmad, Antonios Anastasopoulos, Ondřej Bojar +42

This paper reports on the shared tasks organized by the 21st IWSLT Conference. The shared tasks address 7 scientific challenges in spoken language translation: simultaneous and off…

cs.CL2024

SPES: Spectrogram Perturbation for Explainable Speech-to-Text Generation

Dennis Fucci, Marco Gaido, Beatrice Savoldi +3

Spurred by the demand for interpretable models, research on eXplainable AI for language technologies has experienced significant growth, with feature attribution methods emerging a…

cs.CL2024

MOSEL: 950,000 Hours of Speech Data for Open-Source Speech Foundation Model Training on EU Languages

Marco Gaido, Sara Papi, Luisa Bentivogli +6

The rise of foundation models (FMs), coupled with regulatory efforts addressing their risks and impacts, has sparked significant interest in open-source models. However, existing s…

cs.CL2024

FuxiTranyu: A Multilingual Large Language Model Trained with Balanced Data

Haoran Sun, Renren Jin, Shaoyang Xu +10

Large language models (LLMs) have demonstrated prowess in a wide range of tasks. However, many LLMs exhibit significant performance discrepancies between high- and low-resource lan…

cs.CL2024★ 1 cited

SBAAM! Eliminating Transcript Dependency in Automatic Subtitling

Marco Gaido, Sara Papi, Matteo Negri +2

Subtitling plays a crucial role in enhancing the accessibility of audiovisual content and encompasses three primary subtasks: translating spoken dialogue, segmenting translations i…

cs.CL2023

Integrating Language Models into Direct Speech Translation: An Inference-Time Solution to Control Gender Inflection

Dennis Fucci, Marco Gaido, Sara Papi +3

When translating words referring to the speaker, speech translation (ST) systems should not resort to default masculine generics nor rely on potentially misleading vocal traits. Ra…

cs.CL2023★ 1 cited

No Pitch Left Behind: Addressing Gender Unbalance in Automatic Speech Recognition through Pitch Manipulation

Dennis Fucci, Marco Gaido, Matteo Negri +2

Automatic speech recognition (ASR) systems are known to be sensitive to the sociolinguistic variability of speech data, in which gender plays a crucial role. This can result in dis…

cs.CL2022

Direct Speech Translation for Automatic Subtitling

Sara Papi, Marco Gaido, Alina Karakanta +3

Automatic subtitling is the task of automatically translating the speech of audiovisual content into short pieces of timed text, i.e. subtitles and their corresponding timestamps.…

cs.CL2022

Evaluating Subtitle Segmentation for End-to-end Generation Systems

Alina Karakanta, François Buet, Mauro Cettolo +1

Subtitles appear on screen as short pieces of text, segmented based on formal constraints (length) and syntactic/semantic criteria. Subtitle segmentation can be evaluated with sequ…