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20202026
most citedOver-Generation Cannot Be Rewarded: Length-Adaptive Average Lagging for Simultaneous Speech Translation

18 citations · 97 across the 45 of their papers we have counts for

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Showing 2025Show all

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

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

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

MCIF: Multimodal Crosslingual Instruction-Following Benchmark from Scientific Talks

Sara Papi, Maike Züfle, Marco Gaido +5

Recent advances in large language models have laid the foundation for multimodal LLMs (MLLMs), which unify text, speech, and vision within a single framework. As these models are r…

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

Granary: Speech Recognition and Translation Dataset in 25 European Languages

Nithin Rao Koluguri, Monica Sekoyan, George Zelenfroynd +12

Multi-task and multilingual approaches benefit large models, yet speech processing for low-resource languages remains underexplored due to data scarcity. To address this, we presen…

cs.CL2025

Prepending or Cross-Attention for Speech-to-Text? An Empirical Comparison

Tsz Kin Lam, Marco Gaido, Sara Papi +2

Following the remarkable success of Large Language Models (LLMs) in NLP tasks, there is increasing interest in extending their capabilities to speech -- the most common form of com…

cs.CL2025

NUTSHELL: A Dataset for Abstract Generation from Scientific Talks

Maike Züfle, Sara Papi, Beatrice Savoldi +3

Scientific communication is receiving increasing attention in natural language processing, especially to help researches access, summarize, and generate content. One emerging appli…