Desarrollo de modelos de TAN para las lenguas románicas de la península ibérica

• Autores: Antoni Oliver González, Sergi Alvarez Vidal
• Localización: Procesamiento del lenguaje natural, ISSN 1135-5948, Nº. 76, 2026 (Ejemplar dedicado a: Procesamiento del Lenguaje Natural, Revista nº 76, marzo de 2026), págs. 95-108
• Idioma: español
• Títulos paralelos:
  • Development of NMT Models for the Romance Languages of the Iberian Peninsula
• Enlaces
  • Texto completo
• Resumen
  • español

    This paper presents the final outcomes of the TAN-IBE project, whose central objective has been to develop Neural Machine Translation (NMT) systems specifically adapted for the Romance languages of the Iberian Peninsula, with a particular focus on the most under-resourced among them: Asturian, Aragonese, and Aranese. We present the developed corpora and the final neural machine translation systems trained.

  • español

    En este artículo se presentan los resultados finales del proyecto TANIBE, cuyo objetivo central ha sido diseñar sistemas de traducción automática neuronal (TAN) adaptados a las lenguas románicas de la península ibérica, con una especial atención a aquellas con menos recursos: el asturiano, el aragonés y el aranés. Este artículo se centra en presentar los corpus desarrollados y los modelos de traducción automática neuronal entrenados.

• Referencias bibliográficas
  • Abdurakhmonova, N., A. Z. Mohirdev, M. Salokhiddinov, A. Narzullayev, y A. Gatiatullin. 2024. Nllb-based uzbek nmt: Leveraging multisource...
  • Alves, D. M., J. Pombal, N. M. Guerreiro, P. H. Martins, J. Alves, A. Farajian, B. Peters, R. Rei, P. Fernandes, S. Agrawal, P. Colombo, J....
  • Artetxe, M., G. Labaka, y E. Agirre. 2019. An effective approach to unsupervised machine translation. En Proceedings of the 57th Annual Meeting...
  • Bahdanau, D., K. Cho, y Y. Bengio. 2015. Neural machine translation by jointly learning to align and translate. En Proceedings of the 3rd...
  • Bañóon, M., P. Chen, B. Haddow, K. Heafield, H. Hoang, M. Esplà-Gomis, M. L. Forcada, A. Kamran, P. Koehn, R. Sennrich, y A. Waites. 2020....
  • Bié, L., A. Cerdà-i Cucó, H. Degroote, A. Estela, M. García-Martínez, M. Herranz, A. Kohan, M. Melero, T. O’Dowd, S. O’Gorman, y others. 2020....
  • Burchell, L., O. de Gibert, N. Arefyev [et al.]. 2025. An expanded massive multilingual dataset for high-performance language technologies...
  • Caswell, I., C. Chelba, y N. Constant. 2020. Language id in the wild: Unexpected challenges on the path to a thousandlanguage web text corpus....
  • CE. 1992. European charter for regional or minority languages. European Treaty Series No. 148.
  • Costa-jussà, M. R., J. Cross, O. C¸ elebi, M. Elbayad, K. Heafield, K. Heffernan, E. Kalbassi, J. Lam, D. Licht, J. Maillard, A. Sun, S. Wang,...
  • de Dios-Flores, I., C. Magariños, A. I. Vladu, J. E. Ortega, J. R. Pichel, M. García, P. Gamallo, E. Fernández Rei, A. Bugaríın, M. González...
  • Edunov, S., M. Ott, M. Auli, y D. Grangier. 2018. Understanding back-translation at scale. En Proceedings of the 2018 Conference on Empirical...
  • Fan, A., S. Bhosale, H. Schwenk, Z. Ma, A. El-Kishky, S. Goyal, M. Baines, O. Celebi, G. Wenzek, V. Chaudhary, y et al. 2021. Beyond english-centric...
  • Firat, O., K. Cho, y Y. Bengio. 2016. Multiway, multilingual neural machine translation with a shared attention mechanism. En Proceedings...
  • Forcada, M. L., M. Ginest´ı-Rosell, J. Nordfalk, J. O’Regan, S. Ortiz-Rojas, J. A. P´erez-Ortiz, F. S´anchez-Mart´ınez, G. Ram´ırez-S´anchez,...
  • Garcia Gilabert, J., X. Liao, S. Da Dalt, E. Bohman, A. Mash, F. De Luca Fornaciari, I. Baucells, J. Llop, M. Claramunt, C. Escolano, y M....
  • Gonzalez-Agirre, A., M. Marimon, C. Rodriguez-Penagos, J. Aula-Blasco, I. Baucells, C. Armentano-Oller, J. Palomar-Giner, B. Kulebi, y M....
  • Guzmán, F., P.-J. Chen, M. Ott, J. Pino, G. Lample, M. Lewis, V. Chaudhary, A. Fan, S. Bhosale, N. Goyal, A. El-Kishky, G. Wenzek, A. Chaudhary,...
  • Huck, M. y et al. 2020. Client-side neural machine translation for european languages. En Proceedings of the 28th International Conference...
  • Junczys-Dowmunt, M., R. Grundkiewicz, T. Dwojak, H. Hoang, K. Heafield, T. Neckermann, F. Seide, U. Germann, A. Fikri Aji, N. Bogoychev, A....
  • Junczys-Dowmunt, M., K. Heafield, H. Hoang, R. Grundkiewicz, y A. Aue. 2018b. Marian: Cost-effective highquality neural machine translation...
  • Kingma, D. P. 2014. Adam: A method for stochastic optimization. arXiv preprint arXiv:1412.6980.
  • Koehn, P. y R. Knowles. 2017. Six challenges for neural machine translation. arXiv preprint arXiv:1706.03872. Ar-Xiv:1706.03872.
  • Kornai, A. 2013. Digital language death. PLOS ONE, 8(10):e77056.
  • Kudo, T. y J. Richardson. 2018. Sentencepiece: A simple and language independent subword tokenizer and detokenizer for neural text processing....
  • Lample, G., M. Ott, A. Conneau, L. Denoyer, y M. Ranzato. 2018. Phrase-based & neural unsupervised machine translation. En Proceedings...
  • Li, Z., X. Liu, D. F. Wong, L. S. Chao, y M. Zhang. 2022. Consisttl: Modeling consistency in transfer learning for lowresource neural machine...
  • Nguyen, T. Q. y D. Chiang. 2017. Transfer learning across low-resource, related languages for neural machine translation. En Proceedings of...
  • Oliver, A. y S. ´Alvarez. 2023. Filtering and rescoring the CCMatrix corpus for neural machine translation training. En M. Nurminen J. Brenner...
  • Pan, X., M. Wang, L. Wu, y L. Li. 2021. Contrastive learning for many-to-many multilingual neural machine translation. En Proceedings of the...
  • Papineni, K., S. Roukos, T. Ward, y W.-J. Zhu. 2002. BLEU: a method for automatic evaluation of machine translation. En Proceedings of the...
  • Pérez-Ortiz, J. A., F. Sánchez-Martínez, V. M. Sánchez-Cartagena, M. Esplà-Gomis, A. Galiano-Jiménez, A. Oliver, C. Aventín-Boya, A. Pardos,...
  • Popovic, M. 2016. chrf deconstructed: beta parameters and n-gram weights. En Proceedings of the First Conference on Machine Translation: Volume...
  • Post, M. 2018. A call for clarity in reporting BLEU scores. En Proceedings of the Third Conference on Machine Translation: Research Papers,...
  • Rei, R., C. Stewart, A. C. Farinha, y A. Lavie. 2020. Comet: A neural framework for mt evaluation. En Proceedings of the 2020 Conference on...
  • Reimers, N. y I. Gurevych. 2019. Sentencebert: Sentence embeddings using siamese bert-networks. En Proceedings of the 2019 Conference on Empirical...
  • Sánchez-Martínez, F., J. A. Pérez-Ortiz, A. Galiano-Jiménez, y A. Oliver. 2024. Findings of the wmt 2024 shared task translation into low-resource...
  • Sant, A., D. Bardanca, J. R. Pichel Campos, F. De Luca Fornaciari, C. Escolano, J. Garcia Gilabert, P. Gamallo, A. Mash, X. Liao, y M. Melero....
  • Schwenk, H., G. Wenzek, S. Edunov, ´E. Grave, A. Joulin, y A. Fan. 2021. Ccmatrix: Mining billions of high-quality parallel sentences on the...
  • Sellam, T., D. Das, y A. Parikh. 2020. Bleurt: Learning robust metrics for text generation. En Proceedings of the 58th Annual Meeting of the...
  • Sennrich, R., B. Haddow, y A. Birch. 2016. Improving neural machine translation models with monolingual data. Proceedings of the 54th Annual...
  • Sharami, J. P. R., D. Sterionov, y P. Spronck. 2021. Selecting parallel in-domain sentences for neural machine translation using monolingual...
  • Snover, M., B. Dorr, R. Schwartz, L. Micciulla, y J. Makhoul. 2006. A study of translation edit rate with targeted human annotation. En Proceedings...
  • Tiedemann, J. 2012. Parallel data, tools and interfaces in OPUS. En N. Calzolari K. Choukri T. Declerck M. U. Do˘gan B. Maegaard J. Mariani...
  • Tiedemann, J. y S. Thottingal. 2020. OPUSMT – building open translation services for the world. En A. Martins H. Moniz S. Fumega B. Martins...
  • UNESCO. 2003. Language vitality and endangerment. Informe t´ecnico, UNESCO. Report submitted to the International Expert Meeting on UNESCO...
  • Vaswani, A., N. Shazeer, N. Parmar, J. Uszkoreit, L. Jones, A. N. Gomez, L. Kaiser, y I. Polosukhin. 2017. Attention is all you need. En Proceedings...
  • Wenzek, G., M.-A. Lachaux, A. Conneau, V. Chaudhary, F. Guzm´an, A. Joulin, y E. Grave. 2020. Ccnet: Extracting high quality monolingual datasets...
  • Xu, C., Y. Cui, J. Liu, y et al. 2024. Scaling neural machine translation to 200 languages. Nature.
  • Zoph, B., D. Yuret, J. May, y K. Knight. 2016. Transfer learning for low-resource neural machine translation. En J. Su K. Duh, y X. Carreras,...