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dc.contributor.author Hettige, B
dc.contributor.author Karunananda, AS
dc.date.accessioned 2016-07-15T16:15:20Z
dc.date.available 2016-07-15T16:15:20Z
dc.date.issued 2016-07-15
dc.identifier.uri http://dl.lib.mrt.ac.lk/handle/123/11839
dc.description.abstract This paper presents evaluation methodology for English to Sinhala machine tran slation system. The English to Sinhala machine translation system has been developed by using Multi Agent Approach and powered through the concept of “Varanegeema”. Translation system works through the communication among nine agents namely English Morphological Analyzer Agent, English Parser Agent, English to Sinhala Base Word Translator Agent, Sinhala Morphological Generator Agent, Sinhala Parser agent, Transliteration agent, Intermediate Editor agent, Message Space Agent and Request agent. The evaluation was conducted through three steps. As the first step, evaluation was conducted through the white box testing approach and tested each module in the machine translation system through the developed testing tools. Then, evaluated the system performance and calculated the error rate through the result of the evaluation test bed. Finally, Intelligibility and the Accuracy test will be conducted through the human support. The experimental result shows 89% accuracy of the overall system and 7.2% word error rate and the 5.4% sentence error rate. Details of the evaluation and results are given in the paper en_US
dc.language.iso en en_US
dc.relation.uri http://dx.doi.org/10.1109/ICIAFS.2010.5715630 en_US
dc.source.uri http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=5715630 en_US
dc.subject Machine Translation, Sinhala, Evaluation en_US
dc.title An Evaluation methodology for English to Sinhala machine translation en_US
dc.type Conference-Abstract en_US
dc.identifier.faculty IT en_US
dc.identifier.year 2010 en_US
dc.identifier.conference 5th International Conference on Information and Automation for Sustainability (ICIAFS) en_US
dc.identifier.place Colombo en_US
dc.identifier.pgnos pp. 31 - 36 en_US
dc.identifier.email budditha@yahoo.com en_US
dc.identifier.email asoka@itfac.mrt.ac.lk en_US


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