The Sogou-TIIC Speech Translation System for IWSLT 2018

Yuguang Wang, Liangliang Shi, Linyu Wei, Weifeng Zhu, Jinkun Chen, Zhichao Wang, Shixue Wen, Wei Chen, Yanfeng Wang, Jia Jia

Abstract
This paper describes our speech translation system for the IWSLT 2018 Speech Translation of lectures and TED talks from English to German task. The pipeline approach is employed in our work, which mainly includes the Automatic Speech Recognition (ASR) system, a post-processing module, and the Neural Machine Translation (NMT) system. Our ASR system is an ensemble system of Deep-CNN, BLSTM, TDNN, N-gram Language model with lattice rescoring. We report average results on tst2013, tst2014, tst2015. Our best combination system has an average WER of 6.73. The machine translation system is based on Google’s Transformer architecture. We achieved an improvement of 3.6 BLEU over baseline system by applying several techniques, such as cleaning parallel corpus, fine tuning of single model, ensemble models and re-scoring with additional features. Our final average result on speech translation is 31.02 BLEU.
Anthology ID:
2018.iwslt-1.16
Volume:
Proceedings of the 15th International Conference on Spoken Language Translation
Month:
October 29-30
Year:
2018
Address:
Brussels
Venue:
IWSLT
SIG:
SIGSLT
Publisher:
International Conference on Spoken Language Translation
Note:
Pages:
112–117
Language:
URL:
https://aclanthology.org/2018.iwslt-1.16
DOI:
Bibkey:
Cite (ACL):
Yuguang Wang, Liangliang Shi, Linyu Wei, Weifeng Zhu, Jinkun Chen, Zhichao Wang, Shixue Wen, Wei Chen, Yanfeng Wang, and Jia Jia. 2018. The Sogou-TIIC Speech Translation System for IWSLT 2018. In Proceedings of the 15th International Conference on Spoken Language Translation, pages 112–117, Brussels. International Conference on Spoken Language Translation.
Cite (Informal):
The Sogou-TIIC Speech Translation System for IWSLT 2018 (Wang et al., IWSLT 2018)
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