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  Using support vector machines and state-of-the-art algorithms for phonetic alignment to identify cognates in multi-lingual wordlists

Jäger, G., List, J.-M., & Safroniev, P. (2017). Using support vector machines and state-of-the-art algorithms for phonetic alignment to identify cognates in multi-lingual wordlists. In Association for Computational Linguistics (EACL) (Ed.), Proceedings of the 15. EACL 2017 Software Demonstrations, Valencia, Spain, April 3-7 2017 (pp. 1204-1215). Stroudsburg PA, USA: ACL.

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Item Permalink: https://hdl.handle.net/11858/00-001M-0000-002C-EC45-0 Version Permalink: https://hdl.handle.net/21.11116/0000-0004-97C6-2
Genre: Conference Paper

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 Creators:
Jäger, Gerhard1, Author
List, Johann-Mattis1, Author           
Safroniev, Pavel, Author
Affiliations:
1Computer-Assisted Language Comparison, Max Planck Institute for the Science of Human History, Max Planck Society, ou_2385703              

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Language(s): eng - English
 Dates: 2017-04-03
 Publication Status: Published online
 Pages: 12
 Publishing info: -
 Table of Contents: -
 Rev. Type: -
 Identifiers: Other: shh756
 Degree: -

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Project name : CALC
Grant ID : 715618
Funding program : Horizon 2020 (H2020)
Funding organization : European Commission (EC)

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Title: Proceedings of the 15. EACL 2017 Software Demonstrations, Valencia, Spain, April 3-7 2017
Source Genre: Proceedings
 Creator(s):
Association for Computational Linguistics (EACL), Editor              
Affiliations:
-
Publ. Info: Stroudsburg PA, USA : ACL
Pages: - Volume / Issue: - Sequence Number: - Start / End Page: 1204 - 1215 Identifier: ISBN: 978-1-945626-36-4