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Analysis and Classification of Prosodic Styles in Post-modern Spoken Poetry

  • We present our research on computer-supported analysis of prosodic styles in post-modern poetry. Our project is unique in making use of both the written as well as the spoken form of the poem as read by the original author. In particular, we use speech and natural language processing technology to align speech and text and to perform textual analyses. We then explore, based on literary theory, the quantitative value of various types of features in differentiating various prosodic classes of post-modern poetry using machine-learning techniques. We contrast this feature-driven approach with a theoretically less informed neural networks-based approach and explore the relative strengths of both models, as well as how to integrate higher-level knowledge into the NN. In this paper, we give an overview of our project, our approach, and particularly focus on the challenges encountered and lessons learned in our interdisciplinary endeavour. The classification results of the rhythmical patterns (six classes) using NN-based approaches are better than by feature-based approaches.

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Metadaten
Author:Burkhard Meyer-SickendiekORCiD, Hussein Hussein, Timo BaumannORCiDGND
DOI:https://doi.org/10.18420/infdh2018-09
Parent Title (English):INF-DH 2018 Workshopband
Publisher:Gesellschaft für Informatik e.V
Editor:M. Burghardt, C. Müller-Birn
Document Type:conference proceeding (article)
Language:English
Year of first Publication:2018
Release Date:2022/06/22
Tag:free verse prosody; modern and postmodern poetry; rhythmical patters
Institutes:Fakultät Informatik und Mathematik
Begutachtungsstatus:peer-reviewed
Publication:Externe Publikationen
research focus:Information und Kommunikation
Licence (German):Keine Lizenz - Es gilt das deutsche Urheberrecht: § 53 UrhG