Why don't people use character-level machine translation?

Understand

We present a literature and empirical survey that critically assesses the state of the art in character-level modeling for machine translation (MT).

• Despite evidence in the literature that character-level systems are comparable with subword systems, they are virtually never used in competitive setups in WMT competitions.
• We empirically show that even with recent modeling innovations in character-level natural language processing, character-level MT systems still struggle to match their subword-based counterparts.
• Character-level MT systems show neither better domain robustness, nor better morphological generalization, despite being often so motivated.