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20232026
most citedTranslation in the Hands of Many:Centering Lay Users in Machine Translation Interactions

6 citations · 16 across the 34 of their papers we have counts for

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14 papers · 1 filter

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

Generative AI Practices, Literacy, and Divides: An Empirical Analysis in the Italian Context

Beatrice Savoldi, Giuseppe Attanasio, Olga Gorodetskaya +10

The rise of generative AI (GenAI) chatbots accessible via conversational interfaces is transforming digital interactions and holds economic promise. However, these tools might deep…

cs.CL2025

Voice, Bias, and Coreference: An Interpretability Study of Gender in Speech Translation

Lina Conti, Dennis Fucci, Marco Gaido +3

Unlike text, speech conveys information about the speaker, such as gender, through acoustic cues like pitch. This gives rise to modality-specific bias concerns. For example, in spe…

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

The Unheard Alternative: Contrastive Explanations for Speech-to-Text Models

Lina Conti, Dennis Fucci, Marco Gaido +3

Contrastive explanations, which indicate why an AI system produced one output (the target) instead of another (the foil), are widely regarded in explainable AI as more informative…

cs.CL2025

Gender-Neutral Rewriting in Italian: Models, Approaches, and Trade-offs

Andrea Piergentili, Beatrice Savoldi, Matteo Negri +1

Gender-neutral rewriting (GNR) aims to reformulate text to eliminate unnecessary gender specifications while preserving meaning, a particularly challenging task in grammatical-gend…

cs.CL2025

Cross-Attention is Half Explanation in Speech-to-Text Models

Sara Papi, Dennis Fucci, Marco Gaido +2

Cross-attention is a core mechanism in encoder-decoder architectures, widespread in many fields, including speech-to-text (S2T) processing. Its scores have been repurposed for vari…

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

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

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.CL2025

An LLM-as-a-judge Approach for Scalable Gender-Neutral Translation Evaluation

Andrea Piergentili, Beatrice Savoldi, Matteo Negri +1

Gender-neutral translation (GNT) aims to avoid expressing the gender of human referents when the source text lacks explicit cues about the gender of those referents. Evaluating GNT…

cs.CL2025★ 6 cited

Translation in the Hands of Many:Centering Lay Users in Machine Translation Interactions

Beatrice Savoldi, Alan Ramponi, Matteo Negri +1

Converging societal and technical factors have transformed language technologies into user-facing applications used by the general public across languages. Machine Translation (MT)…