MorphoGen: Full Inflection Generation Using Recurrent Neural Networks

Author:

Şulea Octavia-Maria,Young Steve,Dinu Liviu P.

Publisher

Springer Nature Switzerland

Reference18 articles.

1. Aharoni, R., Goldberg, Y.: Morphological inflection generation with hard monotonic attention. In: Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics, ACL 2017, Vancouver, Canada, July 30 - August 4, Volume 1: Long Papers. pp. 2004–2015 (2017), http://doi.org/10.18653/v1/P17-1183

2. Ahlberg, M., Forsberg, M., Hulden, M.: Paradigm classification in supervised learning of morphology. In: Mihalcea, R., Chai, J.Y., Sarkar, A. (eds.) NAACL HLT 2015, The 2015 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Denver, Colorado, USA, May 31 - June 5, 2015. pp. 1024–1029. The Association for Computational Linguistics (2015), http://aclweb.org/anthology/N/N15/N15-1107.pdf

3. Radford, A., Narasimhan, K., Salimans, T., Sutskever, I.: Improving language understanding by generative pre-training. http://s3-us-west-2.amazonaws.com/openai-assets/research-covers/language-unsupervised/language_understanding_paper.pdf

4. Radford, A., Narasimhan, K., Salimans, T., Sutskever, I.: Language models are unsupervised multitask learners. http://d4mucfpksywv.cloudfront.net/better-language-models/language_models_are_unsupervised_multitask_learners.pdf

5. Barbu, A.M.: Conjugarea verbelor româneşti. Dicţionar: 7500 de verbe româneşti grupate pe clase de conjugare. Bucharest: Coresi (2007), 4th edition, revised. (In Romanian.) (263 pp.)

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