This is a tool to translate an English sentence into Malay and vice versa. Developing a translation tool for low-resource languages like Malay has always been a challenge.
This is a tool to translate an English sentence into Malay and vice versa. Developing a translation tool for low-resource languages like Malay has always been a challenge. The main challenge comes from the fact that machine translation systems typically rely on a huge amount of sentence-parallel data, and creating such datasets is an expensive process. In our work, we collected parallel datasets from various sources including News, OpenSubtitiles (OPUS), Ted talks, and Youtube video. Therefore, our corpus is quite generic and covers both texts and conversations. The second challenge is to train a Machine Learning model. Neural Machine Translation (NMT) is a recently proposed deep learning architecture that has quickly become the standard approach. It offers an end-to-end architecture with better generalization. In the last few years, researchers have proposed many techniques to improve NMT, including work on handling rare words and using attention mechanisms to align input and output words. Our translation system utilizes the most up-to-date NMT architecture, namely the transformer net and the seq2seq architecture. To train our model we used OpenNMT-py framework, which is a standard in the MT community for its robust and modular implementation.