| Autor: |
Byszuk, Joanna, Woźniak, Michal, Kestemont, Mike, Leśniak, Albert, Łukasik, Wojciech, Šeļa, Artjoms, Eder, Maciej |
| Jazyk: |
angličtina |
| Rok vydání: |
2020 |
| Předmět: |
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| Zdroj: |
Proceedings of the 1st Workshop on Language Technologies for Historical and Ancient Languages, (LT4HALA 2020), collocated with LREC 2020. Language Resources and Evaluation Conference 11–16 May 2020 / Sprugnoli, Rachele [edit.]; et al. |
| Popis: |
Fictional prose can be broadly divided into narrative and discursive forms with direct speech being central to any discourse representation (alongside indirect reported speech and free indirect discourse). This distinction is crucial in digital literary studies and enables in - teresting forms of narratological or stylistic analysis. The difficulty of automatically detecting direct speech, however, is currently under-estimated. Rule-based systems that work reasonably well for modern languages struggle with (the lack of) typographical conventions in 19th-century literature. While machine learning approaches to sequence modeling can be applied to solve the task, they typically face a severed skewness in the availability of training material, especially for lesser resourced languages. In this paper, we report the result of a multilingual approach to direct speech detection in a diverse corpus of 19th-century fiction in 9 European languages. The proposed method fine-tunes a transformer architecture with multilingual sentence embedder on a minimal amount of annotated training in each language, and improves performance across languages with ambiguous direct speech marking, in comparison to a carefully constructed regular expression baseline. |
| Databáze: |
OpenAIRE |
| Externí odkaz: |
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