Conditional Random Field Autoencoders for Unsupervised Structured Prediction
Table 1: Left: AER results (%) for Czech-English word alignment. Lower values are better. . Right: Bleu translation quality scores (%) for Czech-English, Urdu-English and Chinese-English. Higher values are better. .
['direction', 'fast_align', 'model 4', 'auto']
Our model significantly outperforms both baselines. This is unsurprising, given that Chinese orthography does not use letters, so that source-language spelling and morphology features our model incorporates introduce only noise here. Better feature engineering, or more data, is called for.