As can be seen from Table 3, the systems using character as WSA outperformed the ones using word as WSA in both small-scale (row 3-5) and large-scale task (row 6-8) with all segmentations.
experiment, our approach consistently outperformed two baselines with three different word segmenters: fully word-based system (using word for both alignment and translation) and fully character-based system, in terms of alignment quality and translation performance.