@InProceedings{agirrezabal-alegria-hulden:2017:RANLP,
  author    = {Agirrezabal, Manex  and  Alegria, I\~{n}aki  and  Hulden, Mans},
  title     = {A Comparison of Feature-Based and Neural Scansion of Poetry},
  booktitle = {Proceedings of the International Conference Recent Advances in Natural Language Processing, RANLP 2017},
  month     = {September},
  year      = {2017},
  address   = {Varna, Bulgaria},
  publisher = {INCOMA Ltd.},
  pages     = {18--23},
  abstract  = {Automatic analysis of poetic rhythm is a challenging task that involves
	linguistics, literature, and computer science. When the language to be analyzed
	is known, rule-based systems or data-driven methods can be used. In this paper,
	we analyze poetic rhythm in English and Spanish. We show that the
	representations of data learned from character-based neural models are more
	informative than the ones from hand-crafted features, and that a
	Bi-LSTM+CRF-model produces state-of-the art accuracy on scansion of poetry in
	two languages. Results also show that the information about whole word
	structure, and not just independent syllables, is highly informative for
	performing scansion.},
  url       = {https://doi.org/10.26615/978-954-452-049-6_003}
}