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https://doi.org/10.21256/zhaw-20082| Publication type: | Conference paper |
| Type of review: | Peer review (publication) |
| Title: | TRANSLIT : a large-scale name transliteration resource |
| Authors: | Benites de Azevedo e Souza, Fernando Duivesteijn, Gilbert François von Däniken, Pius Cieliebak, Mark |
| et. al: | No |
| DOI: | 10.21256/zhaw-20082 |
| Proceedings: | Proceedings of the 12th Conference on Language Resources and Evaluation (LREC 2020) |
| Page(s): | 3265 |
| Pages to: | 3271 |
| Conference details: | 12th Language Resources and Evaluation Conference (LREC), Marseille, France, 11-16 May 2020 |
| Issue Date: | May-2020 |
| Publisher / Ed. Institution: | European Language Resources Association |
| Language: | English |
| Subjects: | Transliteration; Natural language processing; Multi-lingual entities |
| Subject (DDC): | 006: Special computer methods |
| Abstract: | Transliteration is the process of expressing a proper name from a source language in the characters of a target language (e.g. from Cyrillic to Latin characters). We present TRANSLIT, a large-scale corpus with approx. 1.6 million entries in more than 180 languages with about 3 million variations of person and geolocation names. The corpus is based on various public data sources, which have been transformed into a unified format to simplify their usage, plus a newly compiled dataset from Wikipedia. In addition, we apply several machine learning methods to establish baselines for automatically detecting transliterated names in various languages. Our best systems achieve an accuracy of 92\% on identification of transliterated pairs. |
| URI: | https://aclanthology.org/2020.lrec-1.399/ https://digitalcollection.zhaw.ch/handle/11475/20082 |
| Fulltext version: | Published version |
| License (according to publishing contract): | CC BY-NC 4.0: Attribution - Non commercial 4.0 International |
| Departement: | School of Engineering |
| Organisational Unit: | Institute of Computer Science (InIT) |
| Published as part of the ZHAW project: | Libra: A One-Tool Solution for MLD4 Compliance |
| Appears in collections: | Publikationen School of Engineering |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| 2020_Benites-etal_TRANSLIT_LREC.pdf | 206.52 kB | Adobe PDF |  View/Open |
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Benites de Azevedo e Souza, F., Duivesteijn, G. F., von Däniken, P., & Cieliebak, M. (2020). TRANSLIT : a large-scale name transliteration resource [Conference paper]. Proceedings of the 12th Conference on Language Resources and Evaluation (LREC 2020), 3265–3271. https://doi.org/10.21256/zhaw-20082
Benites de Azevedo e Souza, F. et al. (2020) ‘TRANSLIT : a large-scale name transliteration resource’, in Proceedings of the 12th Conference on Language Resources and Evaluation (LREC 2020). European Language Resources Association, pp. 3265–3271. Available at: https://doi.org/10.21256/zhaw-20082.
F. Benites de Azevedo e Souza, G. F. Duivesteijn, P. von Däniken, and M. Cieliebak, “TRANSLIT : a large-scale name transliteration resource,” in Proceedings of the 12th Conference on Language Resources and Evaluation (LREC 2020), May 2020, pp. 3265–3271. doi: 10.21256/zhaw-20082.
BENITES DE AZEVEDO E SOUZA, Fernando, Gilbert François DUIVESTEIJN, Pius VON DÄNIKEN und Mark CIELIEBAK, 2020. TRANSLIT : a large-scale name transliteration resource. In: Proceedings of the 12th Conference on Language Resources and Evaluation (LREC 2020) [online]. Conference paper. European Language Resources Association. Mai 2020. S. 3265–3271. Verfügbar unter: https://aclanthology.org/2020.lrec-1.399/
Benites de Azevedo e Souza, Fernando, Gilbert François Duivesteijn, Pius von Däniken, and Mark Cieliebak. 2020. “TRANSLIT : A Large-Scale Name Transliteration Resource.” Conference paper. In Proceedings of the 12th Conference on Language Resources and Evaluation (LREC 2020), 3265–71. European Language Resources Association. https://doi.org/10.21256/zhaw-20082.
Benites de Azevedo e Souza, Fernando, et al. “TRANSLIT : A Large-Scale Name Transliteration Resource.” Proceedings of the 12th Conference on Language Resources and Evaluation (LREC 2020), European Language Resources Association, 2020, pp. 3265–71, https://doi.org/10.21256/zhaw-20082.
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