The Volctrans Neural Speech Translation System for IWSLT 2021

• URL: http://arxiv.org/abs/2105.07319v1
• Date: Sun, 16 May 2021 00:11:59 GMT
• Title: The Volctrans Neural Speech Translation System for IWSLT 2021
• Authors: Chengqi Zhao and Zhicheng Liu and Jian Tong and Tao Wang and Mingxuan Wang and Rong Ye and Qianqian Dong and Jun Cao and Lei Li
• Abstract summary: This paper describes the systems submitted to IWSLT 2021 by the Volctrans team. For offline speech translation, our best end-to-end model achieves 8.1 BLEU improvements over the benchmark. For text-to-text simultaneous translation, we explore the best practice to optimize the wait-k model.
• Score: 26.058205594318405
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: This paper describes the systems submitted to IWSLT 2021 by the Volctrans team. We participate in the offline speech translation and text-to-text simultaneous translation tracks. For offline speech translation, our best end-to-end model achieves 8.1 BLEU improvements over the benchmark on the MuST-C test set and is even approaching the results of a strong cascade solution. For text-to-text simultaneous translation, we explore the best practice to optimize the wait-k model. As a result, our final submitted systems exceed the benchmark at around 7 BLEU on the same latency regime. We will publish our code and model to facilitate both future research works and industrial applications.

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