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Independent study Report : Improving example based English to Bengali machine translation using WordNet

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dc.contributor.advisor Khan, Mumit
dc.contributor.author Salam, Khan Md. Anwarus
dc.date.accessioned 2010-12-09T03:54:19Z
dc.date.available 2010-12-09T03:54:19Z
dc.date.copyright 2009
dc.date.issued 2009-01
dc.identifier.other ID 07141002
dc.identifier.uri http://hdl.handle.net/10361/677
dc.description This thesis report is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2009.
dc.description Cataloged from PDF version of thesis report.
dc.description Includes bibliographical references (page 32).
dc.description.abstract The goal of this research topic is to develop efficient machine translation system for English to Bengali language by improving my Thesis work “Example Based English to Bengali Machine Translation”. Due to relevance of this work I kept the most of the texts of my thesis. To develop an efficient machine translation system is very important but it is really expensive as it requires a huge amount of time and resources. In all languages there are many words that may have multiple meanings and also some sentence may have multiple grammar structure to express the same meaning, it is a great challenge to do the right semantic analysis. But it is very important to have a machine translation system which can compute all possible outputs in reasonable time and able to choose the best option. We can dramatically improve the performance of English to Bengali Example Based Machine Translation using WordNet. For example the ‘have’ verb has more than ten different meaningful uses during English to Bengali translation. Using the word senses given by WordNet we can dramatically improve the performance of Example Based Machine Translation (EBMT) Depending on various characteristics of words. The proposed EBMT system has five steps: 1) Tagging 2) Parsing 3) Prepare the chunks of the sentence using sub-sentential EBMT 4) Using an efficient adapting scheme match the sentence rule 5) Translate from Source Language (English) to Target Language (Bengali) in the chunk and generate with morphological analysis with the help of WordNet. en_US
dc.description.statementofresponsibility Khan Md. Anwarus Salam
dc.format.extent 32 pages
dc.language.iso en en_US
dc.publisher BRAC University en_US
dc.rights BRAC University thesis are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission.
dc.subject Machine translation en_US
dc.subject WordNet en_US
dc.subject EBMT en_US
dc.subject Example Based en_US
dc.subject Adaptation en_US
dc.subject Computer science and engineering
dc.title Independent study Report : Improving example based English to Bengali machine translation using WordNet en_US
dc.type Thesis en_US
dc.contributor.department Department of Computer Science and Engineering, BRAC University
dc.contributor.department B. Computer Science and Engineering


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