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An Algorithmic Approach to Develop Auto Translation System - Bengali to English
Current Issue
Volume 1, 2014
Issue 4 (September)
Pages: 25-29   |   Vol. 1, No. 4, September 2014   |   Follow on         
Paper in PDF Downloads: 36   Since Aug. 28, 2015 Views: 2064   Since Aug. 28, 2015
Authors
[1]
Md. Ahsan Arif, Department of CSE, Asian University of Bangladesh, Dhaka, Bangladesh.
[2]
Chandni Bhattacharya, Department of CSE, Dhaka University of Engineering and Technology, Dhaka, Bangladesh.
[3]
Abul Barkat Mohammad Abdus Salam, Software Engineer, Solution9 Ltd., Dhaka, Bangladesh.
[4]
Suriya Islam, Graduated from CSE, Asian University of Bangladesh, Dhaka, Bangladesh.
Abstract
In today's globalized world, keeping aware and staying ahead on all sorts of issues from health, environment and energy to political affairs, security and the financial crisis has become a mammoth task. Breaking down language barriers means first-hand access to relevant information that helps to keep the citizen, the policy maker, governmental authorities, the private sector, industry, etc. better informed, especially on fast changing and impacting issues. In the last decade, the working method in Computational Linguistics has evolved to achieve an ultimate goal gradually. Fifteen years back, most of the researches focused on selected example of sentences. Now a day, the information access and utilization of large text is at a common stage. The final output of this research would be like below: Definition of the Bengali’s word/information need; Selection of the Bengali’s natural information sources to be used; Translation of the Bengali user’s query expressed in natural language into the targeting language(English/German/French) of the information source, if necessary; Translation of the Bengali Expression from the Targeting(Foreign) Language to the query language of each information system; Implementation of Bengali Expressions obtained from the query language; Assessment of results by the user and the redefinition of the query expressions if the results are not relevant; and Selecting and obtaining the documents that respond to the user’s needs.
Keywords
Natural Language Processing, Machine Translation, Fuzzy Matching, Computational Linguistics
Reference
[1]
Birch, A. C. Callison-Burch, M. Osborne and P. Koehn. 2006. Constraining the Phrase-Based, Joint Probability Statistical Translation Model. In Proceedings of the Workshop on Statistical Machine Translation, ACL, pages 154–157, New York City.
[2]
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[3]
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[4]
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[5]
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[6]
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[7]
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[8]
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[9]
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