Processing South Asian Languages Written in the Latin Script: the Dakshina Dataset

Brian Roark, Lawrence Wolf-Sonkin, Christo Kirov, Sabrina J. Mielke, Cibu Johny, Isin Demirsahin, Keith Hall


Abstract
This paper describes the Dakshina dataset, a new resource consisting of text in both the Latin and native scripts for 12 South Asian languages. The dataset includes, for each language: 1) native script Wikipedia text; 2) a romanization lexicon; and 3) full sentence parallel data in both a native script of the language and the basic Latin alphabet. We document the methods used for preparation and selection of the Wikipedia text in each language; collection of attested romanizations for sampled lexicons; and manual romanization of held-out sentences from the native script collections. We additionally provide baseline results on several tasks made possible by the dataset, including single word transliteration, full sentence transliteration, and language modeling of native script and romanized text.
Anthology ID:
2020.lrec-1.294
Volume:
Proceedings of the Twelfth Language Resources and Evaluation Conference
Month:
May
Year:
2020
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, Asuncion Moreno, Jan Odijk, Stelios Piperidis
Venue:
LREC
SIG:
Publisher:
European Language Resources Association
Note:
Pages:
2413–2423
Language:
English
URL:
https://aclanthology.org/2020.lrec-1.294
DOI:
Bibkey:
Cite (ACL):
Brian Roark, Lawrence Wolf-Sonkin, Christo Kirov, Sabrina J. Mielke, Cibu Johny, Isin Demirsahin, and Keith Hall. 2020. Processing South Asian Languages Written in the Latin Script: the Dakshina Dataset. In Proceedings of the Twelfth Language Resources and Evaluation Conference, pages 2413–2423, Marseille, France. European Language Resources Association.
Cite (Informal):
Processing South Asian Languages Written in the Latin Script: the Dakshina Dataset (Roark et al., LREC 2020)
Copy Citation:
PDF:
https://aclanthology.org/2020.lrec-1.294.pdf
Code
 google-research-datasets/dakshina
Data
Dakshina