Neural Machine Translation: Assamese–Bengali

Neural machine translation (NMT) is a state-of-the-art technique in the task of machine translation (MT), where a source-language text is converted into a target language text while preserving its meaning. NMT attracts attention because it handles sequence to sequence learning problems for variable-length source and target sentences. With the attention mechanism, the NMT system performs well in the context-analyzing ability. But it needs sufficient parallel training corpus, which is a challenge in low resource language scenario. To overcome the bar of a handy parallel corpus, there is an increase in demand for direct translation among similar language pairs. This paper investigates the NMT system for direct translation of low resource similar language pair: Assamese–Bengali. The main contribution of this work is Assamese–Bengali parallel corpus. The NMT system has achieved a bilingual evaluation understudy (BLEU) score of 7.20 for Assamese to Bengali translation and BLEU score 10.10 for Bengali to Assamese translation, respectively.