Exploiting cross-dialectal gold syntax for low-resource historical languages: towards a generic parser for pre-modern Slavic

Conference item

This paper explores the possibility of improving the performance of specialized parsers for premodern Slavic by training them on data from different related varieties. Because of their linguistic heterogeneity, pre-modern Slavic varieties are treated as low-resource historical languages, whereby cross-dialectal treebank data may be exploited to overcome data scarcity and attempt the training of a variety-agnostic parser. Previous experiments on early Slavic dependency parsing are discussed, particularly with regard to their ability to tackle different orthographic, regional and stylistic features. A generic pre-modern Slavic parser and two specialized parsers – one for East Slavic and one for South Slavic – are trained using jPTDP [8], a neural network model for joint part-of-speech (POS) tagging and dependency parsing which had shown promising results on a number of Universal Dependency (UD) treebanks, including Old Church Slavonic (OCS). With these experiments, a new state of the art is obtained for both OCS (83.79% unlabelled attachment score (UAS) and 78.43% labelled attachment score (LAS)) and Old East Slavic (OES) (85.7% UAS and 80.16% LAS).

Authors: Pedrazzini, N

• Publication status: Published
• Peer review status: Peer reviewed
• Publisher: CEUR Workshop Proceedings
• Host title: Proceedings of the Workshop on Computational Humanities Research (CHR 2020)
• Volume: 2723
• Pages: 237-247
• Publication date: 2020-11-02
• Acceptance date: 2020-08-28
• Event title: CHR 2020: Workshop on Computational Humanities Research
• Event location: Amsterdam, The Netherlands
• Event start date: 2020-11-18
• Event end date: 2020-11-20
• ISSN: 1613-0073
• Language: English
• Keywords: early Slavic; dependency parsing; FFR; low-resource languages; neural networks