Annotating and Classifying Direct Speech in Historical Danish and Norwegian Literary Texts (2025)

Abstract: 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.

## introduction the analysis of direct speech in literary texts provides valuable insights into narrative style, character dynamics as well as aesthetic developments and other broader discourse patterns. in the context of literary history, it has been argued that direct speech, understood as a narrative element that purports to quote a character's speech @xcite , is one of the most distinctive components of modern danish fiction from the late 19 th century @xcite . realist authors of the period use direct speech to reflect characters' social and geographical backgrounds through dialogue rather than explicit description, aiming to portray the fictional world with verisimilitude, i.e. a touch of the real. in scandinavian litera-ture, typographic marking of speech-such as quotation marks, dashes, and colons-is often inconsistent, complicating the task of distinguishing direct speech from narrative text. this is especially true for danish and norwegian novels from the late 19 th century, where typographic conventions are highly variable. while readers can often intuitively recognize direct speech, computational approaches require structured annotation to accurately capture these nuanced typographic and linguistic features @xcite . we introduce a newly annotated dataset derived from the memo corpus @xcite , which includes annotations of speech markers, speech tags and speech separated from other narrative elements across danish and norwegian novels from the late 19 th century. this dataset, annotated on the word level, facilitates the segmentation of direct speech from other narrative elements, enabling sequence tagging model training for the automated detection of these elements. we evaluate several pre-trained language models tailored for danish and norwegian, including the danish foundation models (dfm; @xcite and memo-bert @xcite , to assess their ability to detect direct speech in historical scandinavian texts, and find dfm particularly effective. our findings are of importance to not only literary scholars, but also (socio)linguists who are allowed an indirect access to spoken language from before modern recording technologies @xcite . our contributions are threefold: (1) we present an annotated dataset that captures the typographic and linguistic indicators of direct speech in 19 th century danish and norwegian literature, (2) we conduct an empirical evaluation of state-of-the-art language models fine-tuned on this dataset, and (3) we provide insights into the performance and generalization capabilities of these models for classifying direct speech. 2 related work direct speech identification. identifying direct speech in literary texts has been a focal area in nlp, with various resources and methodologies addressing typographic and linguistic challenges across languages. the swedish literary corpus of narrative and dialogue (slända) exemplifies these efforts, providing annotated excerpts from swedish novels between 1809 and 1940 that capture speech segments, tags, and speaker identification @xcite . in a similar vein, @xcite introduced clause-atlas, a corpus designed to study narrative structure in 19 th and 20 th century english novels, leveraging large language models for clause-based annotation. recent studies have also explored annotation challenges in texts lacking quotation marks. stymne (2024) compared manual (gold) and automated (silver) annotation methods, finding that gold data yields better model performance at the token level, while silver data often excels at capturing speech spans. despite these advancements, most methods rely on monolingual, genre-specific corpora that may not extend well to historical scandinavian languages. historical literary scandinavian nlp. our study builds on recent advances in computational approaches for analyzing historical scandinavian literature, emphasizing the need for tailored datasets and models suited to underresourced languages. allaith et al. (2023 ## experiments and results we model direct speech identification as token classification, i.e. sequence tagging, with the tags described in §3. we fine-tune and evaluate pretrained language models for token classification. ## classifier-assisted corpus analysis we use the top-performing model, dfm (large), to tag all unlabeled segments in the main corpus. this results in 35% of words labeled as speech, 61% as non-speech, 2% as speech markers and 2% as speech tags. figure 1 shows the proportion of speech and non-speech labels over years, illustrating a decreasing trend in the proportion of direct speech over time, with the highest point at 42% in 1874, declining to a low of 29% by 1889. 5 this downward trend stands in contrast to findings from other quantitative studies on direct speech in novels. for example, in the study of british 19 th century novels by @xcite , the overall fraction of dialogue across her entire corpus compares roughly to ours (36%), but she finds no significant change over time. furthermore, our findings challenge the widely held critical assumption within literary historiography that the use of direct speech increased with the rise of the realist novel in the late 19 th century, as argued by @xcite , @xcite , and @xcite . instead, our analysis seems more consistent with the argument presented by @xcite that the french naturalist aesthetic favored free indirect speech over direct speech, leading to a decline of the latter. this perspective aligns more closely with the downward trend we observe in 19 th century scandinavian literature than with the stable levels of direct speech that @xcite reports in british novels from the same period. in other words, based on these quantitative analyses of direct speech, late 19 th century scandinavian novels appear to align more closely with conventional ideas of naturalist narrative techniques than with those of more conventional realist aesthetics. ## conclusion we presented a dedicated dataset and methodology for annotating direct speech in danish and norwegian novels from the late 19 th century, useful for not only literary studies but also for lin-guistics by providing access to representations of 19 th spoken language. by building on the memo corpus, we systematically annotated typographic markers, speech tags, and direct speech segments, addressing the significant variation and inconsistencies in typographic conventions within historical scandinavian literature. through our experiments with multiple language models, including danish foundation models and memo-bert, we found that dfm (large) performed best. using it to quantify the proportion of speech in the main corpus, we observed a decreasing trend over time. future work will extend our analysis to include other variations of speech, namely indirect discourse, i.e. reporting of character speech, and free indirect discourse, namely the incorporation of a character's speech within the narrator's language @xcite . literary-historical research will examine the lexical variations of the speech tags within the corpus to address a hypothesis @xcite ) that a narrative development from "telling" to "showing" in 19 th century literature is manifested in a movement towards greater nuance and lexical variation in the speech tags. while 'telling' is a narrative style, where events are explained explicitly (e.g., 'he was angry'), 'showing' uses a more detailed narrative style to implicitly convey what is at stake in the event, as in 'he slammed his fist on the table and shouted "enough"'. the hypothesis is that this shift is reflected in more nuanced speech tags, moving from simple terms like 'said' to varied ones like 'muttered' or 'snarled.' our code and data are in this github repository: https://github. com/mime-memo/directspeech .