论文标题
神经：神经语音翻译工具包
NeurST: Neural Speech Translation Toolkit
论文作者
论文摘要
Neurst是用于神经语音翻译的开源工具包。该工具包主要集中于端到端的语音翻译，该翻译易于使用，修改并扩展到高级语音翻译研究和产品。 Neurst旨在促进NLP研究人员的语音翻译研究，并为该领域建立可靠的基准。它为特征提取，数据预处理，分布式培训和评估提供分步配方。在本文中，我们将介绍神经局的框架设计，并显示不同基准数据集的实验结果，可以认为这是可靠的基准，用于将来的研究。该工具包可在https://github.com/bytedance/neurst/上公开获取，我们将在https://st-benchmark.githmark.githmark.githmark.io/上不断地更新神经策略的性能。
NeurST is an open-source toolkit for neural speech translation. The toolkit mainly focuses on end-to-end speech translation, which is easy to use, modify, and extend to advanced speech translation research and products. NeurST aims at facilitating the speech translation research for NLP researchers and building reliable benchmarks for this field. It provides step-by-step recipes for feature extraction, data preprocessing, distributed training, and evaluation. In this paper, we will introduce the framework design of NeurST and show experimental results for different benchmark datasets, which can be regarded as reliable baselines for future research. The toolkit is publicly available at https://github.com/bytedance/neurst/ and we will continuously update the performance of NeurST with other counterparts and studies at https://st-benchmark.github.io/.
