FAMA: The First Large-Scale Open-Science Speech Foundation Model for
  English and Italian
Authors: name: Sara Papi, name: Marco Gaido, name: Luisa Bentivogli, name: Alessio Brutti, name: Mauro Cettolo, name: Roberto Gretter, name: Marco Matassoni, name: Mohamed Nabih, name: Matteo Negri

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.