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Automated approach for rhythm analysis of french literary texts

Authors: Elena I. Boychuk; Ilya V. Paramonov; Nikita Kozhemyakin; Natalia Kasatkina;

Automated approach for rhythm analysis of french literary texts

Abstract

Rhythm analysis is widely used for texts in a poetic form to determine the individual style of the author, but rarely used in the analysis of prose due to technical problems and human factor influence. To overcome these issues we propose an automated approach that involves the development and use of specialized software for analyzing French literary prose at various stylistic levels: phonetic, lexical, and grammatical. The methods developed for rhythm analysis and implemented in the computer application cover a variety of the phonostylistic devices: calculation of the length of the rhythmic units, finding assonance, alliteration, rhyme, various repetitions, and others. Efficiency of the approach was proved experimentally by the analysis of rhythmization devices in the novels of four French writers. It was shown that the proposed automated approach allows the researcher to analyze the text 15 times faster than using the manual approach.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
9
Average
Top 10%
Average
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