Proceedings of the Joint 25th Nordic Conference on Computational Linguistics and 11th Baltic Conference on Human Language Technologies (NoDaLiDa/Baltic-HLT 2025)

Sirvi

Nüüd näidatakse 1 - 1 1

Annotating and Classifying Direct Speech in Historical Danish and Norwegian Literary Texts
(University of Tartu Library, 2025-03) Al-Laith, Ali; Conroy, Alexander; Degn, Kirstine Nielsen; Bjerring-Hansen, Jens; Hershcovich, Daniel; Johansson, Richard; Stymne, Sara
Analyzing direct speech in historical literary texts provides insights into character dynamics, narrative style, and discourse patterns. In late 19th century Danish and Norwegian fiction direct speech reflects characters' social and geographical backgrounds. However, inconsistent typographic conventions in Scandinavian literature complicate computational methods for distinguishing direct speech from other narrative elements. To address this, we introduce an annotated dataset from the MeMo corpus, capturing speech markers and tags in Danish and Norwegian novels. We evaluate pre-trained language models for classifying direct speech, with results showing that a Danish Foundation Model (DFM), trained on extensive Danish data, has the highest performance. Finally, we conduct a classifier-assisted quantitative corpus analysis and find a downward trend in the prevalence of speech over time.