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An automated framework for fast cognate detection and Bayesian phylogenetic inference in computational historical linguistics
- Author(s):
- Johann-Mattis List (see profile) , Taraka Rama
- Date:
- 2019
- Group(s):
- Classical Philology and Linguistics, Digital Humanists, History of Linguistics and Language Study, Linguistics
- Subject(s):
- Computational linguistics, Historical linguistics
- Item Type:
- Conference proceeding
- Conf. Title:
- 57th Annual Meeting of the Associacion for Computational Linguistics
- Conf. Org.:
- Association for Computational Linguistics
- Conf. Loc.:
- Florence
- Conf. Date:
- 2019-07-28/2019-08-02
- Tag(s):
- computational historical linguistics, automated sequence comparison, phylogenetic reconstruction
- Permanent URL:
- http://dx.doi.org/10.17613/dqb5-j340
- Abstract:
- We present a fully automated workflow for phylogenetic reconstruction on large datasets, consisting of two novel methods, one for fast detection of cognates and one for fast Bayesian phylogenetic inference. Our results show that the methods take less than a few minutes to process language families that have so far required large amounts of time and computational power. Moreover, the cognates and the trees inferred from the method are quite close, both to gold standard cognate judgments and to expert language family trees. Given its speed and ease of application, our framework is specifically useful for the exploration of very large datasets in historical linguistics.
- Metadata:
- xml
- Status:
- Published
- Last Updated:
- 4 years ago
- License:
- All Rights Reserved
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