A model for English to Urdu and Hindi machine translation system using translation rules and artificial neural network

Abstract EN

This paper illustrates the architecture and working of a proposed multilingual machine translation system which is able to translate from English to Urdu and Hindi.

The system applies translation rules based approach with artificial neural network.

The efficient pattern matching and the ability of learning by examples makes neural networks suitable for implementation of a translation rule based machine translation system.

This paper also describes the importance of machine translation systems and status of the languages in a multilingual country like India.

Machine translation evaluation score for translation output obtained from the system has been calculated using various methods such as n-gram bleu score, F-measure, Meteor and precision, recall.

The evaluation scores achieved by the system for around 500 Hinditest sentences are as: n-gram bleu score 0.5903 ; Metric for Evaluation of Translation with Explicit ORdering (METEOR) score achieved is 0.7956 and F-score of 0.7916 and for Urdu n-gram bleu score achieved by thesystem is 0.6054 ; METEOR score achieved is 0.8083 and F-score of 0.8250.