title: FAMA: The First Large-Scale Open-Science Speech Foundation Model for
    English and Italian
summary: The development of speech foundation models (SFMs) like Whisper and
  SeamlessM4T has significantly advanced the field of speech processing. However,
  their closed nature--with inaccessible training data and code--poses major
  reproducibility and fair evaluation challenges. While other domains have made
  substantial progress toward open science by developing fully transparent models
  trained on open-source (OS) code and data, similar efforts in speech remain
  limited. To fill this gap, we introduce FAMA, the first family of open science
  SFMs for English and Italian, trained on 150k+ hours of OS speech data.
  Moreover, we present a new dataset containing 16k hours of cleaned and
  pseudo-labeled speech for both languages. Results show that FAMA achieves
  competitive performance compared to existing SFMs while being up to 8 times
  faster. All artifacts, including code, datasets, and models, are released under
  OS-compliant licenses, promoting openness in speech technology research.
paper_authors._id: 6839680e3e5dd928f0576da0
paper_authors.name: Sara Papi
paper_authors._id: 6839680e3e5dd928f0576da1
paper_authors.name: Marco Gaido
paper_authors._id: 6839680e3e5dd928f0576da2
paper_authors.name: Luisa Bentivogli
paper_authors._id: 6839680e3e5dd928f0576da3
paper_authors.name: Alessio Brutti
paper_authors._id: 6839680e3e5dd928f0576da4
paper_authors.name: Mauro Cettolo
paper_authors._id: 6839680e3e5dd928f0576da5
paper_authors.name: Roberto Gretter
paper_authors._id: 6839680e3e5dd928f0576da6
paper_authors.name: Marco Matassoni
paper_authors._id: 6839680e3e5dd928f0576da7
paper_authors.name: Mohamed Nabih
paper_authors.status: claimed_verified
paper_authors.statusLastChangedAt: 2025-06-02T07:45:37.798Z
paper_authors._id: 659eab38d55b5c4fa49172d7
paper_authors.avatarUrl: https://cdn-avatars.huggingface.co/v1/production/uploads/659eab38d55b5c4fa49172d7/b6FHt_DIw2rHfcLumjv4f.png
paper_authors.fullname: Mohamed Nabih Ali
paper_authors.type: user
paper_authors.user: mnabihali
paper_authors._id: 6839680e3e5dd928f0576da8
paper_authors.name: Matteo Negri
paper_title: FAMA: The First Large-Scale Open-Science Speech Foundation Model for
    English and Italian
paper_summary: The development of speech foundation models (SFMs) like Whisper and
  SeamlessM4T has significantly advanced the field of speech processing. However,
  their closed nature--with inaccessible training data and code--poses major
  reproducibility and fair evaluation challenges. While other domains have made
  substantial progress toward open science by developing fully transparent models
  trained on open-source (OS) code and data, similar efforts in speech remain
  limited. To fill this gap, we introduce FAMA, the first family of open science
  SFMs for English and Italian, trained on 150k+ hours of OS speech data.
  Moreover, we present a new dataset containing 16k hours of cleaned and
  pseudo-labeled speech for both languages. Results show that FAMA achieves
  competitive performance compared to existing SFMs while being up to 8 times
  faster. All artifacts, including code, datasets, and models, are released under
  OS-compliant licenses, promoting openness in speech technology research.
paper_ai_summary: FAMA, an open science family of speech foundation models, provides transparency and competitive performance by leveraging open-source training data and code.
paper_ai_keywords: speech foundation models Whisper SeamlessM4T open science open-source code open-source data FAMA pseudo-labeled speech