18 citations · 97 across the 45 of their papers we have counts for
54 papers
FBK's Long-form SpeechLLMs for IWSLT 2026 Instruction Following
Zhihang Xie, Marco Gaido, Sara Papi +2
This paper describes our submission to the IWSLT 2026 Instruction Following shared task. SpeechLLMs are developed for both short-form and long-form speech instruction following und…
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…
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…
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…
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…
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…
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…
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…
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…
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…
Speech Foundation Models and Crowdsourcing for Efficient, High-Quality Data Collection
Beomseok Lee, Marco Gaido, Ioan Calapodescu +2
While crowdsourcing is an established solution for facilitating and scaling the collection of speech data, the involvement of non-experts necessitates protocols to ensure final dat…
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…
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…
How to Connect Speech Foundation Models and Large Language Models? What Matters and What Does Not
Francesco Verdini, Pierfrancesco Melucci, Stefano Perna +9
The remarkable performance achieved by Large Language Models (LLM) has driven research efforts to leverage them for a wide range of tasks and input modalities. In speech-to-text (S…
Speech-MASSIVE: A Multilingual Speech Dataset for SLU and Beyond
Beomseok Lee, Ioan Calapodescu, Marco Gaido +2
We present Speech-MASSIVE, a multilingual Spoken Language Understanding (SLU) dataset comprising the speech counterpart for a portion of the MASSIVE textual corpus. Speech-MASSIVE…
SimulSeamless: FBK at IWSLT 2024 Simultaneous Speech Translation
Sara Papi, Marco Gaido, Matteo Negri +1
This paper describes the FBK's participation in the Simultaneous Translation Evaluation Campaign at IWSLT 2024. For this year's submission in the speech-to-text translation (ST) su…
StreamAtt: Direct Streaming Speech-to-Text Translation with Attention-based Audio History Selection
Sara Papi, Marco Gaido, Matteo Negri +1
Streaming speech-to-text translation (StreamST) is the task of automatically translating speech while incrementally receiving an audio stream. Unlike simultaneous ST (SimulST), whi…
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…
How do Hyenas deal with Human Speech? Speech Recognition and Translation with ConfHyena
Marco Gaido, Sara Papi, Matteo Negri +1
The attention mechanism, a cornerstone of state-of-the-art neural models, faces computational hurdles in processing long sequences due to its quadratic complexity. Consequently, re…