Our experiments show that: (1) the encoder with character attention achieves significant improvements over the standard word-based attention-based NMT system and a strong character-based NMT system; (2) incorporating source character information into the decoder by our multi-scale attention mechanism yields a further improvement, and (3) our modifications also improve a subword-based NMT model.
many recent studies have focused on using character-level information in neural machine translation systems.