MOSEL: 950,000 Hours of Speech Data for Open-Source Speech Foundation
  Model Training on EU Languages
Authors: name: Marco Gaido, name: Sara Papi, name: Luisa Bentivogli, name: Alessio Brutti, name: Mauro Cettolo, name: Roberto Gretter, name: Marco Matassoni, name: Mohamed Nabih, name: Matteo Negri

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 speech FMs (SFMs) fall short of full
compliance with the open-source principles, even if claimed otherwise, as no
existing SFM has model weights, code, and training data publicly available
under open-source terms. In this work, we take the first step toward filling
this gap by focusing on the 24 official languages of the European Union (EU).
We collect suitable training data by surveying automatic speech recognition
datasets and unlabeled speech corpora under open-source compliant licenses, for
a total of 950k hours. Additionally, we release automatic transcripts for 441k
hours of unlabeled data under the permissive CC-BY license, thereby
facilitating the creation of open-source SFMs for the EU languages.