---
title: "Language Varieties of Italy — paper by Ramponi (2024)"
description: "The author first describes the linguistic situation, grouping the varieties into macro-areas based on… 3 references, cited by 22 papers here."
authors: ["Alan Ramponi"]
year: 2024
venue: "Transactions of the Association for Computational Linguistics"
source: "https://aclanthology.org/2024.tacl-1.2/"
doi: "10.1162/tacl_a_00631"
licence: "CC BY 4.0 (ACL Anthology)"
licence_url: "https://creativecommons.org/licenses/by/4.0/"
summary_licence: "Elamur Cosmic License"
canonical: "https://research.elamur.ai/free/en/papers/ramponi-2024-language-varieties-italy-technology-challenges/"
---
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# Language Varieties of Italy: Technology Challenges and Opportunities

**Authors:** [Alan Ramponi](https://md.research.elamur.ai/free/en/authors/alan-ramponi/) · **Year:** 2024 · **Venue:** [Transactions of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/tacl/) ([Transactions of the Association for Computational Linguistics (TACL) 2024](https://md.research.elamur.ai/free/en/venues/tacl/2024/)) · **Publisher:** [The MIT Press](https://md.research.elamur.ai/free/en/publishers/the-mit-press/) · **Licence:** [CC BY 4.0 (ACL Anthology)](https://creativecommons.org/licenses/by/4.0/)

**Links:** [Publisher's page](https://aclanthology.org/2024.tacl-1.2/) · [PDF](https://aclanthology.org/2024.tacl-1.2.pdf) · [DOI 10.1162/tacl\_a\_00631](https://doi.org/10.1162/tacl_a_00631) · [OpenAlex](https://openalex.org/W4390740007)

**Citations:** 12 citations (OpenAlex, 2026-10-14) · [22](https://md.research.elamur.ai/free/en/papers/ramponi-2024-language-varieties-italy-technology-challenges/cited-by/) in our library, of the 149,439 papers whose bibliographies we read

## Summary
This position-and-survey paper looks at how NLP handles Italy's endangered local languages and dialects. Italy has one of the densest concentrations of linguistic diversity in Europe, and UNESCO lists more than 30 of its varieties as endangered. The author first describes the linguistic situation, grouping the varieties into macro-areas based on Pellegrini's classic dialect map. He then reviews existing monolingual and multilingual NLP work on these varieties.

The central argument is that current research is machine-centric. It treats the varieties as interchangeable, low-resource versions of standardized languages and assumes they have a stable written form and the same needs as Italian or English. In practice, most varieties are mainly spoken, have no standard orthography, mix with Italian, and fill different social roles.

The paper calls instead for speaker-centric NLP. This means engaging with communities on terms of reciprocity and building technology around what speakers actually need. To support this, the author launched a community initiative and outlines related research directions, such as modeling regional Italian. The work matters as a framework for responsible NLP on endangered and oral languages beyond Italy.

## Key points
- Table 1 lists Italy's UNESCO-endangered varieties with their ISO 639-3 codes, linguistic branch, endangerment level, speaker counts, and whether a standard written form exists. The branches covered are Romance, Germanic, Slavic, Albanian, and Hellenic.
- Usage figures from ISTAT (2017):
  - 45.9% of people speak mostly Italian at home.
  - 32.3% mix Italian with a local language.
  - 14.1% speak mainly a local language.
  - For context, fewer than 10% spoke Italian when the country unified in 1861.
- The paper identifies three machine-centric assumptions:
  - an overemphasis on machine-readable written data;
  - little attention to whether that data represents the speech communities;
  - a uniform view of the functions and needs of different varieties.
- The author launched the community "Varieties of the Boot" (varietiesoftheboot.github.io), along with a GitHub repository that lists language and culture institutes.
- Proposed alternative directions include:
  - NLP for regional Italian, including fairness of models across regional variants;
  - large-scale study of language variation that complements the ALI and AIS linguistic atlases;
  - research on code-switching in its social context.

*Our summary of the paper, in our own words — not its text. The work belongs to its authors; read it at the links above.*

## Institutions

- [Fondazione Bruno Kessler](https://md.research.elamur.ai/free/en/labs/fondazione-bruno-kessler/) — Research institute, Trento, Italy · 35 works · 43,945 citations

📚 Shelves (4): [🖥️ Computer Science](https://md.research.elamur.ai/free/en/shelves/computer-science/) · 16,667 works · [🤖 Artificial Intelligence](https://md.research.elamur.ai/free/en/shelves/computer-science/artificial-intelligence/) · 16,194 works · [🎭 Arts and Humanities](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/) · 16,039 works · [🗣️ Language and Linguistics](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/language-and-linguistics/) · 15,891 works

## Cite

Cite as: Alan Ramponi. 2024. Language Varieties of Italy: Technology Challenges and Opportunities. Transactions of the Association for Computational Linguistics.

The paper itself, not this page. BibTeX from the library's record of the work.

```bibtex
@article{ramponi2024language,
  title = {{Language Varieties of Italy: Technology Challenges and Opportunities}},
  author = {Alan Ramponi},
  journal = {Transactions of the Association for Computational Linguistics},
  year = {2024},
  doi = {10.1162/tacl\_a\_00631},
  url = {https://doi.org/10.1162/tacl_a_00631}
}
```

- [← previous Fire-Flyer AI-HPC: A Cost-Effective Software-Hardware Co-Design for Deep Learning](https://md.research.elamur.ai/free/en/papers/an-2024-fire-flyer-ai-hpc/)
- [next → mCoT: Multilingual Instruction Tuning for Reasoning Consistency in Language Models](https://md.research.elamur.ai/free/en/papers/lai-2024-mcot-multilingual-instruction-tuning-reasoning/)
- [↑ back to papers of 2024](https://md.research.elamur.ai/free/en/papers/2024/page/7/)

## References

3 references, 2 of them with a card of ours. ↗ leads to the work, «find» searches for one we have no id for yet.

1. Julien Abadji, Pedro Ortiz Suarez, Laurent Romary, and Benoı̂t Sagot. 2022. [Towards a cleaner document-oriented multilingual crawled corpus](https://md.research.elamur.ai/free/en/papers/abadji-2022-towards-cleaner-document-oriented-multilingual/). In Proceedings of the Thirteenth Language Resources and Evaluation Conference, pages 4344–4355, Marseille, France. European Language Resources Association.
2. Ahmed Abdelali, Francisco Guzman, Hassan Sajjad, and Stephan Vogel. 2014. [The AMARA corpus: Building parallel language resources for the educational domain](https://md.research.elamur.ai/free/en/papers/abdelali-2014-amara-corpus-building-parallel-language/). In Proceedings of the Ninth International Conference on Language Resources and Evaluation (LREC’14), pages 1856–1862, Reykjavik, Iceland. Europ…
3. Noëmi Aepli, Antonios Anastasopoulos, Adrian-Gabriel Chifu, William Domingues, Fahim Faisal, Mihaela Gaman, Radu Tudor Ionescu, and Yves Scherrer. 2022. Findings of the VarDial evaluation campaign 2022. In Proceedings of the Ninth Workshop on NLP for Similar Languages, Varieties and Dialects, pages… [find](https://scholar.google.com/scholar?q=Noe%CC%88mi+Aepli%2C+Antonios+Anastasopoulos%2C+Adrian%2DGabriel+Chifu%2C+William+Domingues%2C+Fahim+Faisal%2C+Mihaela+Gaman%2C+Radu+Tudor+Ionescu%2C+and+Yves+Scherrer%2E+2022%2E+Findings+of+the+VarDial+evaluation+campaign+20)

*Updated 30 October 2026*
