2026-06-13T17:14:17Zhttp://www.clarin.si/repository/oai/request

oai:www.clarin.si:11356/22012026-05-26T08:26:46Zhdl_11356_1023hdl_11356_1024

The Trankit model for linguistic processing of written and spoken Slovenian 1.3 Krsnik, Luka Dobrovoljc, Kaja Terčon, Luka language model lemmatisation tokenisation sentence segmentation part-of-speech tagging feature prediction parsing dependency parsing corpus annotation This is a retrained Slovenian model for the Trankit v1.1.1 library for multilingual natural language processing (https://pypi.org/project/trankit/), trained on the concatenation of the SSJ UD treebank of written Slovenian (featuring fiction, non-fiction, periodicals and Wikipedia texts) and the SST UD treebank of spoken Slovenian (featuring transcriptions of spontaneous speech in various settings). It is able to predict sentence segmentation, tokenization, lemmatization, language-specific morphological annotation (MULTEXT-East morphosyntactic tags), as well as universal part-of-speech tagging, morphological features, and dependency parses in accordance with the Universal Dependencies annotation scheme (https://universaldependencies.org/). In comparison to its counterpart models trained on SSJ (http://hdl.handle.net/11356/1963) or SST datasets only, this model yields a significantly better performance on spoken transcripts and an identical state-of-the-art performance on written texts. The model can therefore be recommended as the default, 'universal' Trankit model for processing Slovenian, regardless of the data type. To utilize this model, please follow the instructions provided in our github repository (https://github.com/clarinsi/trankit-train) or refer to the Trankit documentation (https://trankit.readthedocs.io/en/latest/training.html#loading). This ZIP file contains models for both xlm-roberta-large (which delivers better performance but requires more hardware resources) and xlm-roberta-base. Version 1.3 was trained on the same data as version 1.2, except that spoken SST data (UD v2.15) was augmented by colloquial (non-standardized) transcriptions of spoken Slovenian alongside the standardized ones. The resulting model achieves state-of-the-art performance on both standardized (e.g. "včasih govorimo takole") and colloquial speech transcriptions (e.g. "včas govorimo tkole"), without affecting the performance on written data. 2026-05-25 toolService http://hdl.handle.net/11356/2201 slv https://doi.org/10.51663/pnz.65.3.01 http://hdl.handle.net/11356/1997 Apache License 2.0 https://opensource.org/licenses/Apache-2.0 PUB text/plain; charset=utf-8 application/zip downloadable_files_count: 1 Centre for Language Resources and Technologies, University of Ljubljana https://github.com/clarinsi/trankit-train