Update results for MUSE in NMT (#396)

Update results for MUSE(parallel multi-scale attention)

english/machine_translation.md

@@ -14,6 +14,7 @@ on BLEU.
 | ------------- | :-----:| --- |
 | Transformer Big + BT (Edunov et al., 2018) | 35.0 | [Understanding Back-Translation at Scale](https://arxiv.org/pdf/1808.09381.pdf) |
 | DeepL | 33.3 | [DeepL Press release](https://www.deepl.com/press.html) |
+| MUSE (Zhao et al., 2019)| 29.9 | [MUSE: Parallel Multi-Scale Attention for Sequence to Sequence Learning](https://arxiv.org/abs/1911.09483) |
 | DynamicConv (Wu et al., 2019)| 29.7 | [Pay Less Attention With Lightweight and Dynamic Convolutions](https://arxiv.org/abs/1901.10430) |
 | AdvSoft + Transformer Big (Wang et al., 2019)| 29.52 | [Improving Neural Language Modeling via Adversarial Training](http://proceedings.mlr.press/v97/wang19f/wang19f.pdf) |
 | Transformer Big (Ott et al., 2018) | 29.3 | [Scaling Neural Machine Translation](https://arxiv.org/abs/1806.00187) |
@@ -32,6 +33,7 @@ on BLEU.
 | ------------- | :-----:| --- |
 | DeepL | 45.9 | [DeepL Press release](https://www.deepl.com/press.html) |
 | Transformer Big + BT (Edunov et al., 2018) | 45.6 | [Understanding Back-Translation at Scale](https://arxiv.org/pdf/1808.09381.pdf) |
+| MUSE (Zhao et al., 2019)| 43.5 | [MUSE: Parallel Multi-Scale Attention for Sequence to Sequence Learning](https://arxiv.org/abs/1911.09483) |
 | DynamicConv (Wu et al., 2019)| 43.2 | [Pay Less Attention With Lightweight and Dynamic Convolutions](https://arxiv.org/abs/1901.10430) |
 | Transformer Big (Ott et al., 2018) | 43.2 | [Scaling Neural Machine Translation](https://arxiv.org/abs/1806.00187) |
 | RNMT+ (Chen et al., 2018) | 41.0* | [The Best of Both Worlds: Combining Recent Advances in Neural Machine Translation](https://arxiv.org/abs/1804.09849) |