Improving the Punjabi-Hindi Braille Neural Machine Translation through Syntax Augmentation

Abstract

The paper describes the development of a neural-based machine translation system for the Punjabi-to-HindiBraille language pair. As no system can directly (on the fly) translate Punjabi (Gurmukhi) text into Bharati Braille, we worked on developing the same. The system was trained on 6 lac parallel corpus. The training corpus of the system incorporated linguistic information along with the parallel text. The system was compared with the baseline NMT system with the syntax-augmented NMT system. The trained system was tested using the standard BLEU MT evaluation metric. The baseline NMT system scored 26.34 while the syntax-augmented NMT system scored 36.66 which was significantly higher than the baseline system.