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Style Detection for Free Verse Poetry from Text and Speech

  • Modern and post-modern free verse poems feature a large and complex variety in their poetic prosodies that falls along a continuum from a more fluent to a more disfluent and choppy style. As the poets of modernism overcame rhyme and meter, they oriented themselves in these two opposing directions, creating a free verse spectrum that calls for new analyses of prosodic forms. We present a method, grounded in philological analysis and current research on cognitive (dis)fluency, for automatically analyzing this spectrum. We define and relate six classes of poetic styles (ranging from parlando to lettristic decomposition) by their gradual differentiation. Based on this discussion, we present a model for automatic prosodic classification of spoken free verse poetry that uses deep hierarchical attention networks to integrate the source text and audio and predict the assigned class. We evaluate our model on a large corpus of German author-read post-modern poetry and find that classes can reliably be differentiated, reaching a weighted f-measure of 0.73, when combining textual and phonetic evidence. In our further analyses, we validate the model’s decision-making process, the philologically hypothesized continuum of fluency and investigate the relative importance of various features.

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Metadaten
Author:Timo BaumannORCiDGND, Hussein Hussein, Burkhard Meyer-SickendiekORCiD
URL / DOI:https://aclanthology.org/C18-1164.pdf
Parent Title (English):Proceedings of the 27th International Conference on Computational Linguistics (COLING), 20-26.08.2018, Santa Fe, New Mexico, USA
Document Type:conference proceeding (article)
Language:English
Year of first Publication:2018
Release Date:2022/06/27
First Page:1929
Last Page:1940
Institutes:Fakultät Informatik und Mathematik
Begutachtungsstatus:peer-reviewed
Publication:Externe Publikationen
research focus:Information und Kommunikation
Licence (German):Creative Commons - CC BY - Namensnennung 4.0 International