Learning Phrase Representations using RNN Encoder–Decoder for Statistical Machine Translation
Table 1: BLEU scores computed on the development and test sets using different combinations of approaches. WP denotes a word penalty, where we penalizes the number of unknown words to neural networks.
['Models', 'BLEU dev', 'BLEU test']
The baseline phrase-based SMT system was built using Moses with default settings. As expected, adding features computed by neural networks consistently improves the performance over the baseline performance.