NDLI: A Hybrid Approach to Sentence Alignment Using Genetic Algorithm

Content Provider	IEEE Xplore Digital Library
Author	Gautam, M. Sinha, R.M.K.
Copyright Year	2007
Description	Author affiliation: Indian Inst. of Technol., Kanpur (Gautam, M.; Sinha, R.M.K.)
Abstract	Sentence alignment in bilingual corpora has been an active research topic in the machine translation research groups. There have been multiple works in the past to align sentences in bilingual corpus in English and European languages and some Asian languages like Chinese and Japanese. This work introduces a novel approach for sentence alignment in bilingual corpora using lexical and statistical information about the language pair using genetic algorithm. The only lexical information used in this work is a restricted form of bilingual dictionary (incomplete). The algorithm works based on the weighted sum of a set of statistical parameters and the parameter denoting degree of dictionary match. No other lexical information like part of speech tagging, chunking, n-gram statistics etc has been used in this work. Our approach has been tested for structurally dissimilar language pair of English-Hindi and is shown to yield a high performance even under noisy conditions. We compare our results with that of Microsoft alignment tool on the same corpus and we find our results to be superior
Sponsorship	Indian Statistical Inst
Starting Page	480
Ending Page	484
File Size	363038
Page Count	5
File Format	PDF
ISBN	0769527701
DOI	10.1109/ICCTA.2007.9
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2007-03-05
Publisher Place	India
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Dictionaries Natural languages Tagging Probability Speech Dynamic programming Statistics Equations Genetic algorithms Testing
Content Type	Text
Resource Type	Article

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