Characterizing the visualization design space of distant and close reading of poetic rhythm
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Published:2023-06-06
Issue:
Volume:6
Page:
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ISSN:2624-909X
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Container-title:Frontiers in Big Data
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language:
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Short-container-title:Front. Big Data
Author:
Benito-Santos Alejandro,Muñoz Salvador,Therón Sánchez Roberto,García Peñalvo Francisco J.
Abstract
Metrical and rhythmical poetry analysis is founded on the systematic statistical analysis and comparison of sonic devices (e.g., rhythmic patterns) that emerge from a combination of pre-established aesthetic and structural rules and the poet's abilities and creative genius to convey a given message adhering to the said constraints. These rhythmical patterns, which have been traditionally obtained by means of a careful close reading of the poems, in a process known as “scansion,” can now be obtained and made visible by automatic means. However, the visualization literature is still scarce on approaches that allow an insightful close and distant reading of the rhythmical patterns in a poetry corpus. In this work, we report our initial efforts in characterizing of the visualization design space of distant and close reading of poetic rhythm. By employing a digital version of a corpus of 11,268 verses originally written by the Spanish poet and playwright Federico García-Lorca (1898–1936), we could craft several prototypical visualizations representative of the inherent complexity of the problem which we expect to employ in future user studies and that we share here with the rest of the community to foster further discussion around this interesting topic.
Funder
H2020 Research Infrastructures
Ministerio de Ciencia, Innovación y Universidades
Publisher
Frontiers Media SA
Subject
Artificial Intelligence,Information Systems,Computer Science (miscellaneous)
Reference27 articles.
1. Rule-based visual mappings –with a case study on poetry visualization;Abdul-Rahman;Comput. Graphics Forum,2013
2. “Machine learning for metrical analysis of english poetry,”;Agirrezabal,2016
3. “A comparison of feature-based and neural scansion of poetry,”;Agirrezabal,2017
4. “Workshop on audio-visual analytics,”;Aigner,2022