@inproceedings{mccurdy-etal-2021-adaptor,
title = "{A}daptor {G}rammars for Unsupervised Paradigm Clustering",
author = "McCurdy, Kate and
Goldwater, Sharon and
Lopez, Adam",
editor = "Nicolai, Garrett and
Gorman, Kyle and
Cotterell, Ryan",
booktitle = "Proceedings of the 18th SIGMORPHON Workshop on Computational Research in Phonetics, Phonology, and Morphology",
month = aug,
year = "2021",
address = "Online",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2021.sigmorphon-1.9",
doi = "10.18653/v1/2021.sigmorphon-1.9",
pages = "82--89",
abstract = "This work describes the Edinburgh submission to the SIGMORPHON 2021 Shared Task 2 on unsupervised morphological paradigm clustering. Given raw text input, the task was to assign each token to a cluster with other tokens from the same paradigm. We use Adaptor Grammar segmentations combined with frequency-based heuristics to predict paradigm clusters. Our system achieved the highest average F1 score across 9 test languages, placing first out of 15 submissions.",
}
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%0 Conference Proceedings
%T Adaptor Grammars for Unsupervised Paradigm Clustering
%A McCurdy, Kate
%A Goldwater, Sharon
%A Lopez, Adam
%Y Nicolai, Garrett
%Y Gorman, Kyle
%Y Cotterell, Ryan
%S Proceedings of the 18th SIGMORPHON Workshop on Computational Research in Phonetics, Phonology, and Morphology
%D 2021
%8 August
%I Association for Computational Linguistics
%C Online
%F mccurdy-etal-2021-adaptor
%X This work describes the Edinburgh submission to the SIGMORPHON 2021 Shared Task 2 on unsupervised morphological paradigm clustering. Given raw text input, the task was to assign each token to a cluster with other tokens from the same paradigm. We use Adaptor Grammar segmentations combined with frequency-based heuristics to predict paradigm clusters. Our system achieved the highest average F1 score across 9 test languages, placing first out of 15 submissions.
%R 10.18653/v1/2021.sigmorphon-1.9
%U https://aclanthology.org/2021.sigmorphon-1.9
%U https://doi.org/10.18653/v1/2021.sigmorphon-1.9
%P 82-89
Markdown (Informal)
[Adaptor Grammars for Unsupervised Paradigm Clustering](https://aclanthology.org/2021.sigmorphon-1.9) (McCurdy et al., SIGMORPHON 2021)
ACL
- Kate McCurdy, Sharon Goldwater, and Adam Lopez. 2021. Adaptor Grammars for Unsupervised Paradigm Clustering. In Proceedings of the 18th SIGMORPHON Workshop on Computational Research in Phonetics, Phonology, and Morphology, pages 82–89, Online. Association for Computational Linguistics.