Automatic Scansion of Spanish Poetry without Syllabification

TL;DR

This paper introduces a novel algorithm for Spanish poetry scansion that accurately analyzes metrics without syllabification, significantly reducing computational costs and outperforming existing methods in speed and accuracy.

Contribution

The authors present a new syllabification-free algorithm for Spanish poetry metric analysis that effectively handles ambiguities and hemistich compensation, improving speed and accuracy.

Findings

Outperforms state-of-the-art in fixed-metre poetry by 2%

Outperforms by 25% in mixed-metre poetry

Runs 21 to 25 times faster than previous methods

Abstract

In recent years, several systems of automated metric analysis of Spanish poetry have emerged. These systems rely on complex methods of syllabification and stress assignment, which use PoS-tagging libraries, whose computational cost is high. This cost increases with the calculation of metric ambiguities. Furthermore, they do not consider determining issues in syllabic count such as the phenomena of compensation between hemistichs of verses of more than eleven syllables. However, it is possible to carry out an informative and accurate metric analysis without using these costly methods. We propose an algorithm that performs accurate scansion (number of syllables, stress pattern and type of verse) without syllabification. It addresses metric ambiguities and takes into account the hemistichs compensation. Our algorithm outperforms the current state of the art by 2% in fixed-metre poetry, and 25% in mixed-metre poetry. It also runs 21 and 25 times faster, respectively. Finally, a desktop application is offered as a tool for researchers of Spanish poetry.