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Computer Science > Computation and Language

arXiv:1711.00938 (cs)
[Submitted on 2 Nov 2017]

Title:A Comparison of Feature-Based and Neural Scansion of Poetry

Authors:Manex Agirrezabal, Iñaki Alegria, Mans Hulden
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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.
Comments: RANLP 2017
Subjects: Computation and Language (cs.CL)
Cite as: arXiv:1711.00938 [cs.CL]
  (or arXiv:1711.00938v1 [cs.CL] for this version)
  https://doi.org/10.48550/arXiv.1711.00938
Related DOI: https://doi.org/10.26615/978-954-452-049-6_003

Submission history

From: Manex Agirrezabal [view email]
[v1] Thu, 2 Nov 2017 21:15:46 UTC (1,524 KB)
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