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Obtaining a minimal set of rewrite rules

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dc.contributor.author Davel, M
dc.contributor.author Barnard, E
dc.date.accessioned 2012-02-23T07:47:21Z
dc.date.available 2012-02-23T07:47:21Z
dc.date.issued 2005-11
dc.identifier.citation Davel, M and Barnard, E. Obtaining a minimal set of rewrite rules. Sixteenth Annual Symposium of the Pattern Recognition Association of South Africa, Langebaan, South Africa, 23-25 November 2005 en_US
dc.identifier.isbn 0-7992-2264-X
dc.identifier.uri http://www.prasa.org/proceedings/2005/prasa05-22.pdf
dc.identifier.uri http://hdl.handle.net/10204/5588
dc.description Sixteenth Annual Symposium of the Pattern Recognition Association of South Africa, Langebaan, South Africa, 23-25 November 2005 en_US
dc.description.abstract In this paper the authors describe a new approach to rewrite rule extraction and analysis, using Minimal Representation Graphs. This approach provides a mechanism for obtaining the smallest possible rule set – within a context-dependent rewrite rule formalism – that describes a set of discrete training data completely, as an indirect approach to obtaining optimal accuracy on an unseen test set. They demonstrate the application of this technique for a pronunciation prediction task. en_US
dc.language.iso en en_US
dc.publisher PRASA en_US
dc.subject Minimal representation graphs en_US
dc.subject Pattern recognition en_US
dc.title Obtaining a minimal set of rewrite rules en_US
dc.type Conference Presentation en_US
dc.identifier.apacitation Davel, M., & Barnard, E. (2005). Obtaining a minimal set of rewrite rules. PRASA. http://hdl.handle.net/10204/5588 en_ZA
dc.identifier.chicagocitation Davel, M, and E Barnard. "Obtaining a minimal set of rewrite rules." (2005): http://hdl.handle.net/10204/5588 en_ZA
dc.identifier.vancouvercitation Davel M, Barnard E, Obtaining a minimal set of rewrite rules; PRASA; 2005. http://hdl.handle.net/10204/5588 . en_ZA
dc.identifier.ris TY - Conference Presentation AU - Davel, M AU - Barnard, E AB - In this paper the authors describe a new approach to rewrite rule extraction and analysis, using Minimal Representation Graphs. This approach provides a mechanism for obtaining the smallest possible rule set – within a context-dependent rewrite rule formalism – that describes a set of discrete training data completely, as an indirect approach to obtaining optimal accuracy on an unseen test set. They demonstrate the application of this technique for a pronunciation prediction task. DA - 2005-11 DB - ResearchSpace DP - CSIR KW - Minimal representation graphs KW - Pattern recognition LK - https://researchspace.csir.co.za PY - 2005 SM - 0-7992-2264-X T1 - Obtaining a minimal set of rewrite rules TI - Obtaining a minimal set of rewrite rules UR - http://hdl.handle.net/10204/5588 ER - en_ZA


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