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.

Phoné: An Initiative to Develop a Dataset for the Automatic Recognition of Spoken Italian / Coro, Gianpaolo; Cutugno, Francesco; Schettino, Loredana; Tanda, Emilia; Vietti, Alessandro; Vitale, VINCENZO NORMAN. - In: ORAL ARCHIVES JOURNAL. - ISSN 3035-4781. - 1:(2025), pp. 89-107. [10.36253/oar-3340]

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

Francesco Cutugno
Co-primo
Writing – Original Draft Preparation
;
Loredana Schettino
Membro del Collaboration Group
;
Emilia Tanda
Writing – Original Draft Preparation
;
Vincenzo Norman Vitale
Conceptualization
2025

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.
2025
Phoné: An Initiative to Develop a Dataset for the Automatic Recognition of Spoken Italian / Coro, Gianpaolo; Cutugno, Francesco; Schettino, Loredana; Tanda, Emilia; Vietti, Alessandro; Vitale, VINCENZO NORMAN. - In: ORAL ARCHIVES JOURNAL. - ISSN 3035-4781. - 1:(2025), pp. 89-107. [10.36253/oar-3340]
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11588/999714
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