@inproceedings{kratochvil-etal-2022-automatic,
title = "Automatic Verb Classifier for {A}bui ({AVC}-abz)",
author = "Kratochvil, Frantisek and
Saad, George and
Vomlel, Ji{\v{r}}{\'\i} and
Kratochv{\'\i}l, V{\'a}clav",
editor = "Ojha, Atul Kr. and
Ahmadi, Sina and
Liu, Chao-Hong and
McCrae, John P.",
booktitle = "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",
month = jun,
year = "2022",
address = "Marseille, France",
publisher = "European Language Resources Association",
url = "https://aclanthology.org/2022.eurali-1.7",
pages = "42--50",
abstract = "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.",
}
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<abstract>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.</abstract>
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%0 Conference Proceedings
%T Automatic Verb Classifier for Abui (AVC-abz)
%A Kratochvil, Frantisek
%A Saad, George
%A Vomlel, Jiří
%A Kratochvíl, Václav
%Y Ojha, Atul Kr.
%Y Ahmadi, Sina
%Y Liu, Chao-Hong
%Y McCrae, John P.
%S 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
%D 2022
%8 June
%I European Language Resources Association
%C Marseille, France
%F kratochvil-etal-2022-automatic
%X 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.
%U https://aclanthology.org/2022.eurali-1.7
%P 42-50
Markdown (Informal)
[Automatic Verb Classifier for Abui (AVC-abz)](https://aclanthology.org/2022.eurali-1.7) (Kratochvil et al., EURALI 2022)
ACL
- Frantisek Kratochvil, George Saad, Jiří Vomlel, and Václav Kratochvíl. 2022. Automatic Verb Classifier for Abui (AVC-abz). In 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, pages 42–50, Marseille, France. European Language Resources Association.