18 citations · 97 across the 45 of their papers we have counts for
51 papers · 1 filter
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…
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…
Speech Translation with Speech Foundation Models and Large Language Models: What is There and What is Missing?
Marco Gaido, Sara Papi, Matteo Negri +1
The field of natural language processing (NLP) has recently witnessed a transformative shift with the emergence of foundation models, particularly Large Language Models (LLMs) that…