Improving the Robustness of Speech Translation

2 Nov 2018Xiang LiHaiyang XueWei ChenYang LiuYang FengQun Liu

Although neural machine translation (NMT) has achieved impressive progress recently, it is usually trained on the clean parallel data set and hence cannot work well when the input sentence is the production of the automatic speech recognition (ASR) system due to the enormous errors in the source. To solve this problem, we propose a simple but effective method to improve the robustness of NMT in the case of speech translation... (read more)

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