Self-attention based end-to-end Hindi-English Neural Machine Translation
Table 3: Model performance in terms of BLEU score on the task of Hindi-English and English-Hindi translation task
['[BOLD] Model', '[BOLD] Hindi-English', '[BOLD] English-Hindi']
From the results which we get, it is evident that the transformer model achieves higher BLEU score than both Attention encoder-decoder and sequence-sequence model. Attention encoder-decoder achieves better BLEU score and sequence-sequence model performs the worst out of the three which further consolidates the point that if we are dealing with long source and target sentences then attention mechanism is very much required to capture long term dependencies and we can solely rely on the attention mechanism, overthrowing recurrent cells completely for the machine translation task.