0561726 20230316105605.320221002235959.9 9 s. P cav_un_epca*0561725978-2-493814-07-442-50ParisEuropean Language Resources Association2022 automatic verb classifier endangered languages head-marking languages Papuan cav_un_auth*0414315 Kratochvíl F. CZ cav_un_auth*0431676 Saad G. CZ cav_un_auth*0101228 Vomlel Jiří UTIA-B Matematická teorie rozhodování Department of Decision Making Theory MTR MTR Department of Decision Making Theory Ústav teorie informace a automatizace AV ČR, v. v. i. cav_un_auth*0216188 Kratochvíl Václav UTIA-B Matematická teorie rozhodování Department of Decision Making Theory MTR MTR Department of Decision Making Theory CZ Ústav teorie informace a automatizace AV ČR, v. v. i. http://library.utia.cas.cz/separaty/2022/MTR/vomlel-0561726.pdf GA20-18407S GA ČR cav_un_auth*0397557 We present an automatic verb classifier system that identifies inflectional classes in Abui (AVC-abz), a Papuan language of the Timor-Alor-Pantar family. The system combines manually annotated language data (the learning set) with the output of a morphological precision grammar (corpus data). The morphological precision grammar is trained on a fully glossed smaller corpus and applied to a larger corpus. Using the k-means algorithm, the system clusters inflectional classes discovered in the learning set. In the second step, Naive Bayes algorithm assigns the verbs found in the corpus data to the best-fitting cluster. AVC-abz serves to advance and refine the grammatical analysis of Abui as well as to monitor corpus coverage and its gradual improvement. cav_un_auth*0437176 Workshop on Resources and Technologies for Indigenous, Endangered and Lesser-resourced Languages in Eurasia 20220620 20220625 Marseille FR AI 60000 60200 60203 2023 4 PR RVO:67985556 https://hdl.handle.net/11104/0335178 cav_un_auth*0304106 Univerzita Palackého v Olomouci, Filozofická fakulta FF UP CZ S 2022 SCOPUS PUBMED WOS cav_un_epca*0561725 Proceedings of the Workshop on Resources and Technologies for Indigenous, Endangered and Lesser-resourced Languages in Eurasia within the 13th Language Resources and Evaluation Conference European Language Resources Association 2022 Paris 42 50 978-2-493814-07-4