Existing systems and approaches for machine translation : a review

Abstract

The Machine Translation has been a branch of Natural Language Processing, which comes under the broad area of Artificial Intelligence. Machine Translation system refers to computer software that translates text or voice from one natural language into another with or without human assistance. Worldwide, large number of machine translation systems have been developed using several approaches including human-assisted, rule-based, statistical, example-based, hybrid and agent based techniques. Among others, Statistical machine translation approach is by far the most widely studied machine translation method in the field of machine translation. The multi-agent approach is a modern approach to handle complexity of the systems in past five years. This paper reviews existing machine translation approaches and systems including existing chine translation systems.