Marco Remón, GuillermoDe la Rosa, JavierGonzalo Arroyo, Julio AntonioRos Muñoz, SalvadorGonzález-Blanco, Elena2025-07-102025-07-102021-03-30G. Marco, J. De La Rosa, J. Gonzalo, S. Ros and E. González-Blanco, "Automated Metric Analysis of Spanish Poetry: Two Complementary Approaches," in IEEE Access, vol. 9, pp. 51734-51746, 2021, https://doi.org/10.1109/ACCESS.2021.30696352169-3536https://doi.org/10.1109/ACCESS.2021.3069635https://hdl.handle.net/20.500.14468/29389This is an Accepted Manuscript of an article published by IEEE Xplore in "IEEE Access, vol. 9, pp. 51734-51746, 2021", available at: https://doi.org/10.1109/ACCESS.2021.3069635 Este es el manuscrito aceptado del artículo publicado por IEEE Xplore en "IEEE Access, vol. 9, pp. 51734-51746, 2021", disponible en línea: https://doi.org/10.1109/ACCESS.2021.3069635The automatic metric analysis (commonly referred to as scansion) of Spanish poetry is not a trivial problem since it combines the nuances of the language, the different poetic traditions related to melodic patterns, and the personal stylistic preferences and intentions of the author. In this paper, we explore two alternative algorithmic approaches tailored to different applications scenarios. The first approach, Rantanplan, is a rule-based method that consists of four Natural Language Processing modules that work together to perform scansion and other related analysis: Part of Speech tagging, syllabification, stress assignment, and metrical adjustment. The second approach, Jumper, explores the possibility of performing scansion without syllabification, with a twofold purpose: to minimize the errors propagated in different parts of the linguistic processing pipeline (including the syllabification step), and to improve the efficiency of the process. Both systems outperform the state of the art and provide either a more informative solution (suitable, for instance, for teaching purposes) or a more efficient processing (when a correct scansion is all the linguistic knowledge required, as in scholar philological studies). The combined use of both systems turns out to provide a practical tool to clean-up manual annotation errors in corpora.eninfo:eu-repo/semantics/openAccess5701.07 Lengua y literatura1203.04 Inteligencia artificialartículonatural language processingdigital humanitiesautomated metric analysisscansioncorpus annotationpoetrySpanish