Vol. 1 (2025)
Speech Technology

Phoné: An Initiative to Develop a Dataset for the Automatic Recognition of Spoken Italian

PDF (Italian)
  • Gianpaolo Coro,
  • Francesco Cutugno,
  • Loredana Schettino,
  • Emilia Tanda,
  • Alessandro Vietti,
  • Vincenzo Norman Vitale
Gianpaolo Coro
Istituto di Scienze e Tecnologie dell’Informazione ‘A. Faedo’ del Consiglio Nazionale delle Ricerche, Pisa, Italia
Francesco Cutugno
Centro Interdipartimentale di ricerca Urban/Eco, Università degli Studi di Napoli Federico II, Italia
Loredana Schettino
Libera Università di Bolzano, Italia
Emilia Tanda
Centro Interdipartimentale di ricerca Urban/Eco, Università degli Studi di Napoli Federico II, Italia
Alessandro Vietti
Libera Università di Bolzano, Italia
Vincenzo Norman Vitale
Centro Interdipartimentale di ricerca Urban/Eco, Università degli Studi di Napoli Federico II, Italia
DOI: https://doi.org/10.36253/oar-3340

Published 2025-02-24

Keywords

  • speech technology,
  • automatic speech recognition,
  • Large Language Models,
  • dataset

How to Cite

Coro, G., Cutugno, F., Schettino, L., Tanda, E., Vietti, A., & Vitale, V. N. (2025). Phoné: An Initiative to Develop a Dataset for the Automatic Recognition of Spoken Italian. Oral Archives Journal, 1, 89–107. https://doi.org/10.36253/oar-3340

Copyright (c) 2025 Gianpaolo Coro, Francesco Cutugno, Loredana Schettino, Emilia Tanda, Alessandro Vietti, Vincenzo Norman Vitale

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

Abstract

Large Language Models (LLM) have revolutionised natural language processing and its applications. However, high-performance LLMs require copious data and computing resources for their development and are rarely public. This also concerns Large Acoustic Models (LAM) for processing spoken language. The Phoné initiative seeks to build an open Italian speech dataset to advance Automatic Speech Recognition (ASR) systems and support public research. Spearheaded by institutions in Naples, Pisa, and Bolzano, the project gathers diverse Italian audio sources and applies advanced ASR architectures, including supervised and self-supervised models. This paper details Phoné’s dataset creation, ASR model evaluation, and ethical considerations, aiming to democratise access to Italian-language resources and foster innovation in ASR technologies.

PDF (Italian)

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