18 citations · 96 across the 44 of their papers we have counts for
12 papers · 2 filters
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…
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…
Hearing to Translate: The Effectiveness of Speech Modality Integration into LLMs
Sara Papi, Javier Garcia Gilabert, Zachary Hopton +8
As Large Language Models (LLMs) expand beyond text, integrating speech as a native modality has given rise to SpeechLLMs, which directly process spoken language and enable speech-t…
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…
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…
Better Late Than Never: Meta-Evaluation of Latency Metrics for Simultaneous Speech-to-Text Translation
Peter Polák, Sara Papi, Luisa Bentivogli +1
Simultaneous speech-to-text translation systems must balance translation quality with latency. Although quality evaluation is well established, latency measurement remains a challe…
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…
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…
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…
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…
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…
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…