Non-linear Learning for Statistical Machine Translation

IJCNLP 2015 Shujian Huang Huadong Chen Xin-yu Dai Jia-Jun Chen

Modern statistical machine translation (SMT) systems usually use a linear combination of features to model the quality of each translation hypothesis. The linear combination assumes that all the features are in a linear relationship and constrains that each feature interacts with the rest features in an linear manner, which might limit the expressive power of the model and lead to a under-fit model on the current data... (read more)

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