One Sentence One Model for Neural Machine Translation

Understand

Neural machine translation (NMT) becomes a new state-of-the-art and achieves promising translation results using a simple encoder-decoder neural network.

• This neural network is trained once on the parallel corpus and the fixed network is used to translate all the test sentences.
• We argue that the general fixed network cannot best fit the specific test sentences.
• In this paper, we propose the dynamic NMT which learns a general network as usual, and then fine-tunes the network for each test sentence.