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Deep Learning meets Post-modern Poetry

  • We summarize our project Rhythmicalizer in which we analyze a corpus of post-modern poetry in a combination of qualitative hermeneutical and computational methods, as we have run the project over the course of the past three years (and preparing it for some time before that). Interdisciplinary work is always challenging and we here focus on some of the highlights of our collaboration.

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Metadaten
Author:Timo BaumannORCiDGND, Burkhard Meyer-SickendiekORCiD
URL / DOI:http://ceur-ws.org/Vol-2717/paper03.pdf
ISSN:1613-0073
Parent Title (English):TwinTalks 2020: Understanding and Facilitating Collaboration in Digital Humanities 2020, proceedings of the Twin Talks 2 and 3 workshops at DHN 2020 and DH 2020, Ottawa Canada and Riga Latvia, July 23 and October 20, 2020
Publisher:RWTH Aachen
Editor:Steven Krauwer, Darja Fišer
Document Type:conference proceeding (article)
Language:English
Year of first Publication:2020
Release Date:2022/04/11
Tag:Literary Studies; Machine Learning; Meta-Research
First Page:30
Last Page:36
Andere Schriftenreihe:CEUR Workshop Proceedings ; 2717
Institutes:Fakultät Informatik und Mathematik
Begutachtungsstatus:peer-reviewed
Publication:Externe Publikationen
OpenAccess Publikationsweg:Gold Open Access- Erstveröffentlichung in einem/als Open-Access-Medium
research focus:Information und Kommunikation
Licence (German):Creative Commons - CC BY - Namensnennung 4.0 International