Abstract
In this paper we present the final result of a project focused on Tunisian Arabic encoded in Arabizi, the Latin-based writing system for digital conversations. The project led to the realization of two integrated and independent tools: a linguistic corpus and a neural network architecture created to annotate the former with various levels of linguistic information (code-switching classification, transliteration, tokenization, POS-tagging, lemmatization). We discuss the choices made in terms of computational and linguistic methodology and the strategies adopted to improve our results. We report on the experiments performed in order to outline our research path. Finally, we explain the reasons why we believe in the potential of these tools for both computational and linguistic researches.- Anthology ID:
- 2022.lrec-1.121
- Volume:
- Proceedings of the Thirteenth Language Resources and Evaluation Conference
- Month:
- June
- Year:
- 2022
- Address:
- Marseille, France
- Editors:
- Nicoletta Calzolari, Frédéric Béchet, Philippe Blache, Khalid Choukri, Christopher Cieri, Thierry Declerck, Sara Goggi, Hitoshi Isahara, Bente Maegaard, Joseph Mariani, Hélène Mazo, Jan Odijk, Stelios Piperidis
- Venue:
- LREC
- SIG:
- Publisher:
- European Language Resources Association
- Note:
- Pages:
- 1125–1136
- Language:
- URL:
- https://aclanthology.org/2022.lrec-1.121
- DOI:
- Cite (ACL):
- Elisa Gugliotta and Marco Dinarelli. 2022. TArC: Tunisian Arabish Corpus, First complete release. In Proceedings of the Thirteenth Language Resources and Evaluation Conference, pages 1125–1136, Marseille, France. European Language Resources Association.
- Cite (Informal):
- TArC: Tunisian Arabish Corpus, First complete release (Gugliotta & Dinarelli, LREC 2022)
- PDF:
- https://preview.aclanthology.org/emnlp22-frontmatter/2022.lrec-1.121.pdf
- Data
- TArC