Abstract
We applied a new method for the identification of fuzzy periods and the insertion and deletion of characters were taken into consideration while studying the works of poetry. The technique employs genetic algorithm, dynamic programming, and the Monte Carlo method. In the present work, the technique was applied to poems written by the famous Russian and foreign classics. A total of 95 poems were studied; and fuzzy periods possessing high statistical significance were identified with more than half of the poems under study. The existence of correlation between the stressed vowel letters in a poem with the position of the fuzzy periods was shown. The present study shows that a work of poetry contains both semantic component and fuzzy periods of letters; hence a poem could have psychological impact on the audience.
Highlights
Works of poetry could be considered as a superposition of the semantic content and of the acoustic wave determined by a certain sound alternation periodicity
If the meaning of a poetic text is understood by each person, the acoustic wave embedded in a work of poetry will be perceived rather intuitively, as some musicality, often fascinating the listeners and exposing them to a certain psychological impact [1]
In order to understand the mechanism of the acoustic wave impact on listeners, it would be very interesting to attempt quantitatively identifying and studying the acoustic wave embedded in a work of poetry, in the form of a certain periodicity of the poetic text [2, 3]
Summary
Works of poetry could be considered as a superposition of the semantic content and of the acoustic wave determined by a certain sound alternation periodicity. There are mathematical approaches based on dynamic programming that allow the accurate identification of fuzzy periods of time series or character sequence in the presence of characters insertion or deletion [9, 10] All these techniques are used to construct the multiple alignment of periods; and they are based either on performing the pairwise alignment of periods, followed by the subsequent creation of a guide tree, or on the search for embryos or common words in periods. This method employs genetic algorithm, techniques aimed at optimizing weight matrices, dynamic programming, and the Monte Carlo method It enables identification of the fuzzy periods of a character sequence with insertions and deletions in previously unknown positions.
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