English-Indonesian phrase translation using recurrent neural network and adj technique

Abstract

Recurrent Neural Network (RNN) and annotated disjunction are discussed to develop English-Indonesian phrase based. Phrase-based English-Indonesian machine translation becomes important because there are differences between two languages and it can be a sub system for English-Indonesian machine translation. Automatic translation can be done using RNN and ADJ Technique. The main process in this research are preprocessing, determination of phrase type, and translation the phrase. In the preprocessing has process such as case folding, tokenizing, pos tagging, and stemming. In the determination of phrase type, system counts weight of input phrase using RNN. The translation phrase is entered to target language using ADJ Technique. The software experiment is tested by using 70 English phrases. The result shows accuracy of RNN and ADJ Technique for English-Indonesian phrase translation is 88.57 %.