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Machine Translation Approaches: Issues and Challenges

Margaret Dumebi Okpor

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Abstract

In the modern world, there is an increased need for language translations owing to the fact that language is an effective medium of communication. The demand for translation has become more in recent years due to increase in the exchange of information between various regions using different regional languages. Accessibility to web document in other languages, for instance, has been a concern for information Professionals. Machine translation (MT), a subfield under Artificial Intelligence, is the application of computers to the task of translating texts from one natural (human) language to another. Many approaches have been used in the recent times to develop an MT system. Each of these approaches has its own advantages and challenges. This paper takes a look at these approaches with the few of identifying their individual features, challenges and the best domain they are best suited to.

Topics & Concepts

Machine translationComputer scienceArtificial intelligenceTask (project management)Natural language processingDomain (mathematical analysis)Natural languageData scienceEngineeringMathematicsSystems engineeringMathematical analysisNatural Language Processing TechniquesTopic ModelingSemantic Web and Ontologies
Machine Translation Approaches: Issues and Challenges | Litcius