Language Identification for Multilingual Machine Translation

Machine translation is the process of translating a text in one natural language into another natural language using computer system. Translating a document containing a single source language contents is easy but when the information in the source document is given in multilingual format then there is a need to identify the languages that are involved in such multilingual document. Language identification is the task in natural language processing that automatically identifies the natural language in which the content in given document are written in. Language identification is the fundamental and crucial step in many NLP applications. In this paper, n-gram based and machine learning based language identifiers are trained and used to identify three Indian languages such as Hindi, Marathi and Sanskrit present in a document given for machine translation. It is observed that, support vector machine based language identifier is more accurate than any other technique and it achieves 89% accuracy that is 18% more than traditional n-gram based approach. The inclusion of language identification component in machine translation improved the quality of translation.