Title: An English to Urdu translation model based on CBR, ANN and translation rules
Authors: Shahnawaz; R.B. Mishra
Addresses: College of Computation and Informatics, Saudi Electronic University, Dammam, 31454, Saudi Arabia ' Department of Computer Engineering, Indian Institute of Technology, Banaras Hindu University (IT-BHU), Varanasi, U.P., 221005, India
Abstract: In this paper, a model has been presented for English to Urdu machine translation based on case-based reasoning (CBR) technique for machine translation (MT), translation rule base model and artificial neural network (ANN) model. This paper describes the architecture and working of the MT system. We have used translation rules-based case marking for inflection of words according to the number, person and gender in the target language. The CBR approach is used as learning technique for the selection of Urdu translation rules for the input English sentence. The integration of rule-based model with CBR combines the representation and reasoning. Neural network adds the retrieval and learning processes in the computation for machine translation. The rule-based model enhances the adaptation process. The translation results obtained from the system have been evaluated and achieved an average n-gram BLEU score 0.728, meteor score 0.869, F-measure score 0.894, unigram precision 0.923 and unigram recall 0.909.
Keywords: English translation; artificial neural networks; case-based reasoning; CBR; translation rules; machine translation; English to Urdu translation; ANNs.
International Journal of Advanced Intelligence Paradigms, 2015 Vol.7 No.1, pp.1 - 23
Received: 08 Jan 2014
Accepted: 17 Sep 2014
Published online: 02 Jul 2015 *