A Statistical Model for Lost Language Decipherment
URL to paper listed on conference site
| Main Authors: | , , |
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| Other Authors: | |
| Format: | Article |
| Language: | en_US |
| Published: |
Association for Computational Linguistics
2011
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| Online Access: | http://hdl.handle.net/1721.1/62802 https://orcid.org/0000-0002-2921-8201 |
| _version_ | 1811085244013477888 |
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| author | Snyder, Benjamin Barzilay, Regina Knight, Kevin |
| author2 | Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory |
| author_facet | Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory Snyder, Benjamin Barzilay, Regina Knight, Kevin |
| author_sort | Snyder, Benjamin |
| collection | MIT |
| description | URL to paper listed on conference site |
| first_indexed | 2024-09-23T13:05:52Z |
| format | Article |
| id | mit-1721.1/62802 |
| institution | Massachusetts Institute of Technology |
| language | en_US |
| last_indexed | 2024-09-23T13:05:52Z |
| publishDate | 2011 |
| publisher | Association for Computational Linguistics |
| record_format | dspace |
| spelling | mit-1721.1/628022022-10-01T13:00:05Z A Statistical Model for Lost Language Decipherment Snyder, Benjamin Barzilay, Regina Knight, Kevin Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science Barzilay, Regina Snyder, Benjamin Barzilay, Regina URL to paper listed on conference site In this paper we propose a method for the automatic decipherment of lost langauges. Given a non-parallel corpus in a known related language, our model produces both alphabetic mappings and translations of words into their corresponding cognates. We employ a non-parametric Bayesian framework to simultaneously capture both low-level character mappings and high-level morphemic correspondences. This formulation enables us to encode some of the linguistic intuitions that have guided human decipherers. When applied to the ancient Semitic language Ugaritic, the model correctly maps nearly all letters to their Hebrew counterparts, and deduces the correct Hebrew cognate for over half of the Ugaritic words which have cognates in Hebrew. National Science Foundation (U.S.) (CAREER grant IIS-0448168) National Science Foundation (U.S.) (Career award IIS 0835445) 2011-05-10T17:57:45Z 2011-05-10T17:57:45Z 2010-07 Article http://purl.org/eprint/type/ConferencePaper http://hdl.handle.net/1721.1/62802 Snyder, Benjamin, Regina Barzilay and Kevin Knight. "A Statistical Model for Lost Language Decipherment." in ACL 2010, 48th Annual Meeting of the Association for Computational Linguistics, Uppsala, Sweden, July 11–16, 2010. https://orcid.org/0000-0002-2921-8201 en_US http://acl2010.org/program_mainconf.html#s86 Proceedings of the 48th Annual Meeting of the Association for Computational Linguistics, ACL 2010 Creative Commons Attribution-Noncommercial-Share Alike 3.0 http://creativecommons.org/licenses/by-nc-sa/3.0/ application/pdf Association for Computational Linguistics MIT web domain |
| spellingShingle | Snyder, Benjamin Barzilay, Regina Knight, Kevin A Statistical Model for Lost Language Decipherment |
| title | A Statistical Model for Lost Language Decipherment |
| title_full | A Statistical Model for Lost Language Decipherment |
| title_fullStr | A Statistical Model for Lost Language Decipherment |
| title_full_unstemmed | A Statistical Model for Lost Language Decipherment |
| title_short | A Statistical Model for Lost Language Decipherment |
| title_sort | statistical model for lost language decipherment |
| url | http://hdl.handle.net/1721.1/62802 https://orcid.org/0000-0002-2921-8201 |
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