Poesiaren eskantsio automatikoabi hizkuntzen azterketa

  1. Manex Agirrezabal Zabaleta
  2. Iñaki Alegria Loinaz
  3. Mans Hulden
Book:
II. Ikergazte nazioarteko ikerketa euskaraz: Kongresuko artikulu-bilduma.
  1. Iñaki Alegria (ed. lit.)
  2. Ainhoa Latatu (ed. lit.)
  3. Miren Josu Omaetxebarria (ed. lit.)
  4. Patxi Salaberri (ed. lit.)

Publisher: Udako Euskal Unibertsitatea, UEU = Universidad Vasca de Verano

ISBN: 978-84-8438-627-8,  978-84-8438-628-5

Year of publication: 2017

Volume Title: Giza Zientziak eta Artea

Tome: 1

Volume: 1

Pages: 48-55

Congress: Ikergazte. Nazioarteko Ikerketa Euskaraz (2. 2017. Iruñea)

Type: Conference paper

DOI: 10.26876/IKERGAZTE.II.01.06 DIALNET GOOGLE SCHOLAR lock_openOpen access editor

Sustainable development goals

Abstract

In this work we perform automatic scansion —the act of metrically representing a line of verse— ofpoetry. We employ typical Natural Language Processing techniques and go further by using current DeepLearning models. We have tested our systems in two languages; English and Spanish. We got our bestresults with the Deep Learning frameworks, both in English and Spanish. Furthermore, we can concludethat the scansion of poetry in English is more complex than in Spanish. We intend to apply these modelson Basque poetry.

Data source: Dialnet