2016 MorphologicalInflectionGenerati

• (Faruqui et al., 2016) ⇒ Manaal Faruqui, Yulia Tsvetkov, Graham Neubig, and Chris Dyer. (2016). “Morphological Inflection Generation Using Character Sequence to Sequence Learning.” In: Proceedings of the 2016 Conference of the North {A}merican Chapter of the Association for Computational Linguistics: Human Language Technologies. DOI:10.18653/v1/N16-1077

Subject Headings: Encoder-Decoder Neural Network; Morphological Inflection Task; Morphological Inflection Encode-Decoder Neural Network, Seq2Seq Neural Network, Character Seq2Seq Neural Network.

Notes

• Article Versions and URLs:
  • ACL Anthology: N16-1077.
  • DBLP Computer Science Bibliography: FaruquiTND16.
  • ArXiv: 1512.06110 (First pre-print published in 2015).
  • photron.com PDF: PDF file.

Cited By

• Google Scholar: ~ 81 Citations
• Semantic Scholar: ~ 90 Citations

Quotes

Abstract

Morphological inflection generation is the task of generating the inflected form of a given lemma corresponding to a particular linguistic transformation. We model the problem of inflection generation as a character sequence to sequence learning problem and present a variant of the neural encoder-decoder model for solving it. Our model is language independent and can be trained in both supervised and semi-supervised settings. We evaluate our system on seven datasets of morphologically rich languages and achieve either better or comparable results to existing state-of-the-art models of inflection generation.

---

---

References

;

	Author	volume	Date Value	title	type	journal	titleUrl	doi	note	year
2016 MorphologicalInflectionGenerati	Chris Dyer Graham Neubig Manaal Faruqui Yulia Tsvetkov			Morphological Inflection Generation Using Character Sequence to Sequence Learning				10.18653/v1/N16-1077		2016