Memory-enhanced Decoder For Neural Machine Translation
Mingxuan Wang, Zhengdong Lu, Hang Li, Qun Liu . Proceedings of the 2016 Conference on Empirical Methods in Natural Language Processing 2016 – 63 citations
We propose to enhance the RNN decoder in a neural machine translator (NMT) with external memory, as a natural but powerful extension to the state in the decoding RNN. This memory-enhanced RNN decoder is called \textsc{MemDec}. At each time during decoding, \textsc{MemDec} will read from this memory and write to this memory once, both with content-based addressing. Unlike the unbounded memory in previous work\cite{RNNsearch} to store the representation of source sentence, the memory in \textsc{MemDec} is a matrix with pre-determined size designed to better capture the information important for the decoding process at each time step. Our empirical study on Chinese-English translation shows that it can improve by (4.8) BLEU upon Groundhog and (5.3) BLEU upon on Moses, yielding the best performance achieved with the same training set.