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        <title>Using Global Constraints and Reranking to Improve Cognates Detection</title>
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            <title>Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)</title>
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    <abstract>Global constraints and reranking have not been used in cognates detection research to date. We propose methods for using global constraints by performing rescoring of the score matrices produced by state of the art cognates detection systems. Using global constraints to perform rescoring is complementary to state of the art methods for performing cognates detection and results in significant performance improvements beyond current state of the art performance on publicly available datasets with different language pairs and various conditions such as different levels of baseline state of the art performance and different data size conditions, including with more realistic large data size conditions than have been evaluated with in the past.</abstract>
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    <identifier type="doi">10.18653/v1/P17-1181</identifier>
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%0 Conference Proceedings
%T Using Global Constraints and Reranking to Improve Cognates Detection
%A Bloodgood, Michael
%A Strauss, Benjamin
%Y Barzilay, Regina
%Y Kan, Min-Yen
%S Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
%D 2017
%8 July
%I Association for Computational Linguistics
%C Vancouver, Canada
%F bloodgood-strauss-2017-using
%X Global constraints and reranking have not been used in cognates detection research to date. We propose methods for using global constraints by performing rescoring of the score matrices produced by state of the art cognates detection systems. Using global constraints to perform rescoring is complementary to state of the art methods for performing cognates detection and results in significant performance improvements beyond current state of the art performance on publicly available datasets with different language pairs and various conditions such as different levels of baseline state of the art performance and different data size conditions, including with more realistic large data size conditions than have been evaluated with in the past.
%R 10.18653/v1/P17-1181
%U https://aclanthology.org/P17-1181
%U https://doi.org/10.18653/v1/P17-1181
%P 1983-1992

Markdown (Informal)

[Using Global Constraints and Reranking to Improve Cognates Detection](https://aclanthology.org/P17-1181) (Bloodgood & Strauss, ACL 2017)

• Using Global Constraints and Reranking to Improve Cognates Detection (Bloodgood & Strauss, ACL 2017)

ACL

• Michael Bloodgood and Benjamin Strauss. 2017. Using Global Constraints and Reranking to Improve Cognates Detection. In Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), pages 1983–1992, Vancouver, Canada. Association for Computational Linguistics.