A Survey on Spoken Italian Datasets and Corpora
Marco Giordano, Claudia Rinaldi
TL;DR
This survey tackles the fragmentation and underrepresentation of Italian spoken-language resources by cataloging 66 datasets and organizing them across speech types, sources, and demographic/linguistic features. It systematically reviews data collection, annotation, and validation practices, and maps datasets to applications in ASR, TTS, translation, sentiment analysis, and education. Key contributions include a structured inventory, insights into best practices and limitations, and actionable recommendations for standardization, openness, and collaboration to accelerate Italian speech technology development. By providing an open-access resource and highlighting gaps—especially in dialectal and minority-language coverage—the work supports researchers and developers in building robust, inclusive Italian language technologies with broader societal impact.
Abstract
Spoken language datasets are vital for advancing linguistic research, Natural Language Processing, and speech technology. However, resources dedicated to Italian, a linguistically rich and diverse Romance language, remain underexplored compared to major languages like English or Mandarin. This survey provides a comprehensive analysis of 66 spoken Italian datasets, highlighting their characteristics, methodologies, and applications. The datasets are categorized by speech type, source and context, and demographic and linguistic features, with a focus on their utility in fields such as Automatic Speech Recognition, emotion detection, and education. Challenges related to dataset scarcity, representativeness, and accessibility are discussed alongside recommendations for enhancing dataset creation and utilization. The full dataset inventory is publicly accessible via GitHub and archived on Zenodo, serving as a valuable resource for researchers and developers. By addressing current gaps and proposing future directions, this work aims to support the advancement of Italian speech technologies and linguistic research.