# A Survey on Spoken Italian Datasets and Corpora

arXiv: https://arxiv.org/abs/2501.06557 · HTML: https://mlsanity.com/paper/2501.06557/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 13 of its 69 references that are in the map.
- First posted on arXiv 11 Jan 2025.

## Builds on (most cited first, 13 of 13)

- [Robust Speech Recognition via Large-Scale Weak Supervision](https://mlsanity.com/paper/2212.04356/) (2022)
- [WavLM: Large-Scale Self-Supervised Pre-Training for Full Stack Speech Processing](https://mlsanity.com/paper/2110.13900/) (2021)
- [MLS: A Large-Scale Multilingual Dataset for Speech Research](https://mlsanity.com/paper/2012.03411/) (2020)
- [VoxPopuli: A Large-Scale Multilingual Speech Corpus for Representation Learning, Semi-Supervised Learning and Interpretation](https://mlsanity.com/paper/2101.00390/) (2021)
- [Speak, Read and Prompt: High-Fidelity Text-to-Speech with Minimal Supervision](https://mlsanity.com/paper/2302.03540/) (2023)
- [Europarl-ST: A Multilingual Corpus For Speech Translation Of Parliamentary Debates](https://mlsanity.com/paper/1911.03167/) (2019)
- [Hey ASR System! Why Aren't You More Inclusive? Automatic Speech Recognition Systems' Bias and Proposed Bias Mitigation Techniques. A Literature Review](https://mlsanity.com/paper/2211.09511/) (2022)
- [ITALIC: An Italian Intent Classification Dataset](https://mlsanity.com/paper/2306.08502/) (2023)
- [Analysis of Deep Clustering as Preprocessing for Automatic Speech Recognition of Sparsely Overlapping Speech](https://mlsanity.com/paper/1905.03500/) (2019)
- [Custom Data Augmentation for low resource ASR using Bark and Retrieval-Based Voice Conversion](https://mlsanity.com/paper/2311.14836/) (2023)
- [Speech Analysis of Language Varieties in Italy](https://mlsanity.com/paper/2406.15862/) (2024)
- [Consonant gemination in Italian: the nasal and liquid case](https://mlsanity.com/paper/2005.06960/) (2020)
- [RECOApy: Data recording, pre-processing and phonetic transcription for end-to-end speech-based applications](https://mlsanity.com/paper/2009.05493/) (2020)

## Abstract (arXiv)

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.