The DOI matches its Crossref record.
Grammar-based Data Augmentation for Low-Resource Languages: The Case of Guarani-Spanish Neural Machine Translation
Open accessAbstract
Agustín Lucas, Alexis Baladón, Victoria Pardiñas, Marvin Agüero-Torales, Santiago Góngora, Luis Chiruzzo. Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers). 2024.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
The source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“This approach, led by researchers in Uruguay, achieved better translation accuracy by leveraging linguistic knowledge of Guaraní morphology (which is highly agglutinative).”
From Data colonialism and indigenous languages in AI: a critical review of existing initiatives and their struggles with data sovereignty (2026) · cites this paper as Lucas et al. 2024
Experimental — accuracy not yet measuredThe cited source says what the claim attributes to it.
In the citing paper
“For example, a 2024 study used grammar-based data augmentation to improve a neural Guaraní-Spanish translator, artificially generating Guaraní sentences from grammatical rules to supplement scarce training data (Lucas et al. 2024).”
From Data colonialism and indigenous languages in AI: a critical review of existing initiatives and their struggles with data sovereignty (2026) · cites this paper as Lucas et al. 2024
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
No references could be resolved yet.
Research works printed but not linked: 33
- Marvin M Agüero-Torales, Antonio G López-Herrera, and David Vilares. 2023. Multidimensional affective analysis for low-resource languages: A use case with guarani-spanish code-switching language. Cognitive Computation, 15(4):1391-1406. · DOI
- Aldo Alvarez. 2019. Linguistic hackathon: Accelerat- ing bilingual data generation through collaboration for guarani-spanish language pair. In Presentation at 8th Podlasie Conference on Mathematics (8th PCM), Białystok, Poland.
- Juan Aparicio, Mariona Taulé, and M. Antònia Martí. 2008. AnCora-verb: A lexical resource for the se- mantic annotation of corpora. In Proceedings of the Sixth International Conference on Language Re- sources and Evaluation (LREC'08), Marrakech, Mo- rocco. European Language Resources Association (ELRA).
- James Bergstra and Yoshua Bengio. 2012. Random search for hyper-parameter optimization. Journal of Machine Learning Research, 13(10):281-305.
- editor, Cultural Worlds of the Jesuits in Colonial Latin America, pages 127-145. London University Press. Institute of Latin American Studies.
- Laurie Burchell, Alexandra Birch, and Kenneth Heafield. 2022. Exploring diversity in back trans- lation for low-resource machine translation. In Pro- ceedings of the Third Workshop on Deep Learning for Low-Resource Natural Language Processing, pages 67-79, Hybrid. Association for Computational Lin- guistics. · DOI
- Luis Chiruzzo, Marvin Agüero-Torales, Aldo Alvarez, and Yliana Rodríguez. 2023a. Initial experiments for building a Guarani WordNet. In Proceedings of the 12th Global Wordnet Conference, pages 197- 204, University of the Basque Country, Donostia -San Sebastian, Basque Country. Global Wordnet Association.
- Luis Chiruzzo, Marvin Agüero-Torales, Gustavo Giménez-Lugo, Aldo Alvarez, Yliana Rodríguez, Santiago Góngora, and Thamar Solorio. 2023b. Overview of gua-spa at iberlef 2023: Guarani- spanish code switching analysis. Procesamiento del Lenguaje Natural, 71(0):321-328.
- Luis Chiruzzo, Pedro Amarilla, Adolfo Ríos, and Gustavo Giménez Lugo. 2020. Development of a Guarani -Spanish parallel corpus. In Proceedings of the Twelfth Language Resources and Evaluation Conference, pages 2629-2633, Marseille, France. Eu- ropean Language Resources Association.
- Luis Chiruzzo, Santiago Góngora, Aldo Alvarez, Gus- tavo Giménez-Lugo, Marvin Agüero-Torales, and Yliana Rodríguez. 2022a. Jojajovai: A parallel Guarani-Spanish corpus for MT benchmarking. In Proceedings of the Thirteenth Language Resources and Evaluation Conference, pages 2098-2107, Mar- seille, France. European Language Resources Asso- ciation.
- Luis Chiruzzo, Euan McGill, Santiago Egea-Gómez, and Horacio Saggion. 2022b. Translating Spanish into Spanish Sign Language: Combining rules and data-driven approaches. In Proceedings of the Fifth Workshop on Technologies for Machine Translation of Low-Resource Languages (LoResMT 2022), pages 75-83, Gyeongju, Republic of Korea. Association for Computational Linguistics.
- Abteen Ebrahimi, Manuel Mager, Arturo Oncevay, Vishrav Chaudhary, Luis Chiruzzo, Angela Fan, John Ortega, Ricardo Ramos, Annette Rios, Ivan Vladimir Meza Ruiz, Gustavo Giménez-Lugo, Elisabeth Mager, Graham Neubig, Alexis Palmer, Rolando Coto-Solano, Thang Vu, and Katharina Kann. 2022. AmericasNLI: Evaluating zero-shot natural language understanding of pretrained multilingual models in truly low-resource languages. In Proceedings of the 60th Annual Meeting of the Association for Compu- tational Linguistics (Volume 1: Long Papers), pages 6279-6299, Dublin, Ireland. Association for Compu- tational Linguistics. · DOI
- Abteen Ebrahimi, Manuel Mager, Shruti Rijhwani, Enora Rice, Arturo Oncevay, Claudia Baltazar, María Cortés, Cynthia Montaño, John E. Ortega, Rolando Coto-solano, Hilaria Cruz, Alexis Palmer, and Katha- rina Kann. 2023. Findings of the AmericasNLP 2023 shared task on machine translation into indige- nous languages. In Proceedings of the Workshop on Natural Language Processing for Indigenous Lan- guages of the Americas (AmericasNLP), pages 206- 219, Toronto, Canada. Association for Computational Linguistics. · DOI
- Bruno Estigarribia. 2015. Guarani-spanish jopara mix- ing in a paraguayan novel: Does it reflect a third language, a language variety, or true codeswitching? Journal of Language Contact, 8(2):183-222.
- Marzieh Fadaee, Arianna Bisazza, and Christof Monz. 2017. Data augmentation for low-resource neural machine translation. In Proceedings of the 55th An- nual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers), pages 567-573, Vancouver, Canada. Association for Computational Linguistics. · DOI · Paper page
- Santiago Góngora, Nicolás Giossa, and Luis Chiruzzo. 2021. Experiments on a Guarani corpus of news and social media. In Proceedings of the First Work- shop on Natural Language Processing for Indigenous Languages of the Americas, pages 153-158, Online. Association for Computational Linguistics. · DOI
- Santiago Góngora, Nicolás Giossa, and Luis Chiruzzo. 2022. Can we use word embeddings for enhancing Guarani-Spanish machine translation? In Proceed- ings of the Fifth Workshop on the Use of Compu- tational Methods in the Study of Endangered Lan- guages, pages 127-132, Dublin, Ireland. Association for Computational Linguistics. · DOI
- Zexue He, Graeme Blackwood, Rameswar Panda, Julian McAuley, and Rogerio Feris. 2023. Synthetic pre- training tasks for neural machine translation. In Find- ings of the Association for Computational Linguis- tics: ACL 2023, pages 8080-8098, Toronto, Canada. Association for Computational Linguistics. · DOI
- Alexander Jones, Isaac Caswell, Orhan Firat, and Is- hank Saxena. 2023. GATITOS: Using a new multi- lingual lexicon for low-resource machine translation. In Proceedings of the 2023 Conference on Empiri- cal Methods in Natural Language Processing, pages 371-405, Singapore. Association for Computational Linguistics.
- Pratik Joshi, Sebastin Santy, Amar Budhiraja, Kalika Bali, and Monojit Choudhury. 2020. The state and fate of linguistic diversity and inclusion in the NLP world. In Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, pages 6282-6293, Online. Association for Computational Linguistics. · DOI · Paper page
- Marcin Junczys-Dowmunt, Roman Grundkiewicz, Tomasz Dwojak, Hieu Hoang, Kenneth Heafield, Tom Neckermann, Frank Seide, Ulrich Germann, Alham Fikri Aji, Nikolay Bogoychev, André F. T. Martins, and Alexandra Birch. 2018. Marian: Fast neural machine translation in C++. In Proceedings of ACL 2018, System Demonstrations, pages 116-121, Melbourne, Australia. Association for Computational Linguistics.
- Guillaume Klein, Yoon Kim, Yuntian Deng, Jean Senel- lart, and Alexander Rush. 2017. OpenNMT: Open- source toolkit for neural machine translation. In Pro- ceedings of ACL 2017, System Demonstrations, pages 67-72, Vancouver, Canada. Association for Compu- tational Linguistics.
- Philipp Koehn and Rebecca Knowles. 2017. Six chal- lenges for neural machine translation. In Proceedings of the First Workshop on Neural Machine Translation, pages 28-39, Vancouver. Association for Computa- tional Linguistics. · DOI · Paper page
- Manuel Mager, Rajat Bhatnagar, Graham Neubig, Ngoc Thang Vu, and Katharina Kann. 2023. Neural machine translation for the indigenous languages of the Americas: An introduction. In Proceedings of the Workshop on Natural Language Processing for Indigenous Languages of the Americas (Americas- NLP), pages 109-133, Toronto, Canada. Association for Computational Linguistics. · DOI
- Manuel Mager, Arturo Oncevay, Abteen Ebrahimi, John Ortega, Annette Rios, Angela Fan, Ximena Gutierrez- Vasques, Luis Chiruzzo, Gustavo Giménez-Lugo, Ri- cardo Ramos, Ivan Vladimir Meza Ruiz, Rolando Coto-Solano, Alexis Palmer, Elisabeth Mager-Hois, Vishrav Chaudhary, Graham Neubig, Ngoc Thang Vu, and Katharina Kann. 2021. Findings of the Ameri- casNLP 2021 shared task on open machine transla- tion for indigenous languages of the Americas. In Proceedings of the First Workshop on Natural Lan- guage Processing for Indigenous Languages of the Americas, pages 202-217, Online. Association for Computational Linguistics. · DOI
- Sergio Nesmachnow and Santiago Iturriaga. 2019. Cluster-uy: Collaborative scientific high performance computing in uruguay. In Supercomputing, pages 188-202, Cham. Springer International Publishing.
- Lluís Padró and Evgeny Stanilovsky. 2012. FreeLing 3.0: Towards wider multilinguality. In Proceed- ings of the Eighth International Conference on Lan- guage Resources and Evaluation (LREC'12), pages 2473-2479, Istanbul, Turkey. European Language Resources Association (ELRA).
- Kishore Papineni, Salim Roukos, Todd Ward, and Wei- Jing Zhu. 2002. Bleu: a method for automatic evalu- ation of machine translation. In Proceedings of the 40th Annual Meeting of the Association for Compu- tational Linguistics, pages 311-318, Philadelphia, Pennsylvania, USA. Association for Computational Linguistics. · DOI · Paper page
- Carl Pollard and Ivan A Sag. 1994. Head-driven phrase structure grammar. University of Chicago Press.
- Maja Popović. 2015. chrF: character n-gram F-score for automatic MT evaluation. In Proceedings of the Tenth Workshop on Statistical Machine Translation, pages 392-395, Lisbon, Portugal. Association for Computational Linguistics. · DOI · Paper page
- Matt Post. 2018. A call for clarity in reporting BLEU scores. In Proceedings of the Third Conference on Machine Translation: Research Papers, pages 186- 191, Brussels, Belgium. Association for Computa- tional Linguistics. · DOI · Paper page
- Víctor M. Sánchez-Cartagena, Miquel Esplà-Gomis, Juan Antonio Pérez-Ortiz, and Felipe Sánchez- Martínez. 2021. Rethinking data augmentation for low-resource neural machine translation: A multi- task learning approach. In Proceedings of the 2021 Conference on Empirical Methods in Natural Lan- guage Processing, pages 8502-8516, Online and Punta Cana, Dominican Republic. Association for Computational Linguistics. · DOI
- Rico Sennrich, Barry Haddow, and Alexandra Birch. 2016. Improving neural machine translation models with monolingual data. In Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), pages 86-96, Berlin, Germany. Association for Computational Lin- guistics. · DOI · Paper page
Cited by
Sorted by citations
Kwok, J. C. Y. (2026) · AI & SOCIETY · doi:10.1007/s00146-026-03091-w · Cited by 4
Metadata
- Authors
- Lucas, A., Baladón, A., Pardiñas, V., Agüero-Torales, M., Góngora, S., & Chiruzzo, L.
- Affiliations
- Universidad de la República de Uruguay (UY)
- Universidad de Granada (ES)
- Venue
- Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers)
- Published
- 2024
- Pages
- 6385-6397
- OpenAlex
- W4401042669
- Cited by
- 5
- References
- 0
- Citations by year
- 2026: 4 · 2025: 1
- FWCI
- 1.44
- Type
- conference paper
- Language
- en
- Open access
- hybrid
- dx.doi.org
- Licence
- cc-by
- Locations
- Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (NAACL-HLT) (publishedVersion, cc-by)
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Natural Language Processing Techniques
- Physical Sciences › Computer Science › Artificial Intelligence › Topic Modeling
- Physical Sciences › Computer Science › Artificial Intelligence › Speech Recognition and Synthesis
- Keywords
- low-resource languages, Guarani, Spanish language, neural machine translation, parallel corpus construction, morphologically rich languages
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review