A Hybrid Approach for Word Alignment in English-Hindi Parallel Corpora with Scarce Resources

This paper presents an approach which improves the performance of the word alignment with scarce resources for English-Hindi language pair. We obtain an improvement in the performance of IBM Model 1-2 algorithm by applying part of speech (POS) tag prior to the computation of word alignment probabili...

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Bibliographic Details
Published in2012 International Conference on Asian Language Processing (IALP) pp. 185 - 188
Main Authors Srivastava, J., Sanyal, S.
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.11.2012
Subjects
Computational linguistics
Computational modeling
Error analysis
Hidden Markov models
Information technology
POS tagger
Scarce resources
Statistical Machine Translation
Tagging
Training
Word alignment
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ISBN9781467361132
1467361135
DOI10.1109/IALP.2012.13

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Summary:This paper presents an approach which improves the performance of the word alignment with scarce resources for English-Hindi language pair. We obtain an improvement in the performance of IBM Model 1-2 algorithm by applying part of speech (POS) tag prior to the computation of word alignment probability. This paper demonstrates the increase of precision, recall and F-measure by approximately 15%, 11%, 14% respectively and reduction in Alignment Error Rate (AER) by approximately 14% with IBM Model 1. Similarly it shows an increase of precision, recall and F-measure by approximately 6%, 6% and 6% respectively and reduction in Alignment Error Rate (AER) by approximately 6% with IBM Model 2. Experiments of this paper are based on TDIL corpus.
ISBN:9781467361132
1467361135
DOI:10.1109/IALP.2012.13