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Found 7 papers, 2 papers with code
Improving Context-aware Neural Machine Translation with Target-side Context
We propose a weight sharing method wherein NMT saves decoder states and calculates an attention vector using the saved states when translating a current sentence.
Filtering Pseudo-References by Paraphrasing for Automatic Evaluation of Machine Translation
We use the outputs of off-the-shelf MT systems as pseudo-references filtered by paraphrasing in addition to a single human reference (gold reference).
Multimodal Machine Translation with Embedding Prediction
Multimodal machine translation is an attractive application of neural machine translation (NMT).
Graph-based Filtering of Out-of-Vocabulary Words for Encoder-Decoder Models
For Japanese-to-English translation, this method achieves a BLEU score that is 0. 56 points more than that of a baseline.
Japanese Predicate Conjugation for Neural Machine Translation
Neural machine translation (NMT) has a drawback in that can generate only high-frequency words owing to the computational costs of the softmax function in the output layer.
Improving Japanese-to-English Neural Machine Translation by Voice Prediction
This study reports an attempt to predict the voice of reference using the information from the input sentences or previous input/output sentences.
Controlling the Voice of a Sentence in Japanese-to-English Neural Machine Translation
The results showed that, we could control the voice of the generated sentence with 85. 0{\%} accuracy on average.
