An Automated Framework for Fast Cognate Detection and Bayesian Phylogenetic Inference in Computational Historical Linguistics (P19-1)
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| Challenge: | Existing methods for phylogenetic reconstruction of large datasets require time and computational power. |
| Approach: | They propose a workflow for phylogenetic reconstruction on large datasets using two methods . they use a method for fast detection of cognates and a Bayesian method for inference . their results show that the methods take less than a few minutes to process language families . |
| Outcome: | The proposed methods are fast and easy to use and close to gold standard cognate judgments and expert language family trees. |
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| Challenge: | Phylogenetic trees are hypotheses of how sets of related languages evolved in time. |
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| Challenge: | Existing cognate databases have limited practical applications for research, despite their wide coverage and limited use in lexical tasks. |
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Liviu Dinu, Ana Uban, Alina Cristea, Ioan-Bogdan Iordache, Teodor-George Marchitan, Simona Georgescu, Laurentiu Zoicas
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Liviu Dinu, Ana Uban, Alina Cristea, Anca Dinu, Ioan-Bogdan Iordache, Simona Georgescu, Laurentiu Zoicas
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| Challenge: | Existing methods for cognate identification are based on distributions of phonemes and make little use of cognacy labels. |
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Liviu P. Dinu, Ana Sabina Uban, Ioan-Bogdan Iordache, Alina Maria Cristea, Simona Georgescu, Laurentiu Zoicas
| Challenge: | Existing methods for discriminating between cognates and borrowings are difficult, but they provide a deeper insight into the history of a language and allow for a better characterization of language relatedness. |
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| Challenge: | Workshop on Commonsense Inference in Natural Language Processing focuses on commonsense knowledge representation and application in NLP tasks. |
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Transactions of the Association for Computational Linguistics, Volume 8 (2020.tacl-1)
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| Challenge: | null |
| Approach: | null |
| Outcome: | null |
BDPROTO: A Database of Phonological Inventories from Ancient and Reconstructed Languages (L18-1)
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| Challenge: | BDPROTO is a database of phonological inventory data from 137 ancient and reconstructed languages. |
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Harnessing Cross-lingual Features to Improve Cognate Detection for Low-resource Languages (2020.coling-main)
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Diptesh Kanojia, Raj Dabre, Shubham Dewangan, Pushpak Bhattacharyya, Gholamreza Haffari, Malhar Kulkarni
| Challenge: | a study of 14 Indian languages shows that cognates can be detected by word embeddings . cognates are variants of the same lexical form across languages . |
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