Machine translation is an inevitable field of
Natural Language Processing, which includes two steps.
The first step literally follows the reference method of
machine translation, taking advantage of corpus of
knowledge already available in the system. The second step
involves the post-editing done by human intervention. This
paper analyzes the errors, categorizes them, and gives a
comparative study of the errors in the first and second steps.
Further, this analysis is done in a multilingual environment.
Every step is accompanied by the machine training on the
corpus of annotations and systematic classifiers.
Real Time Impact Factor:
Pending
Author Name: S.Sivakama Sundari, V.Prema, G.Savitha
URL: View PDF
Keywords: Machine Translation, Machine Learning, Classifiers, Post-editing, multilingual environment.
ISSN: 2394-7179
EISSN: 2394-7187
EOI/DOI:
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