Hongjie Chen


2018

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Alibaba Speech Translation Systems for IWSLT 2018
Nguyen Bach | Hongjie Chen | Kai Fan | Cheung-Chi Leung | Bo Li | Chongjia Ni | Rong Tong | Pei Zhang | Boxing Chen | Bin Ma | Fei Huang
Proceedings of the 15th International Conference on Spoken Language Translation

This work describes the En→De Alibaba speech translation system developed for the evaluation campaign of the International Workshop on Spoken Language Translation (IWSLT) 2018. In order to improve ASR performance, multiple ASR models including conventional and end-to-end models are built, then we apply model fusion in the final step. ASR pre and post-processing techniques such as speech segmentation, punctuation insertion, and sentence splitting are found to be very useful for MT. We also employed most techniques that have proven effective during the WMT 2018 evaluation, such as BPE, back translation, data selection, model ensembling and reranking. These ASR and MT techniques, combined, improve the speech translation quality significantly.