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NeurST: Neural Speech Translation Toolkit

About

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/.

Chengqi Zhao, Mingxuan Wang, Qianqian Dong, Rong Ye, Lei Li• 2020

Related benchmarks

TaskDatasetResultRank
Speech TranslationMuST-C EN-DE (test-COMMON)
BLEU22.8
41
Speech TranslationMuST-C (test)--
29
Speech TranslationMuST-C EN-FR COMMON (test)
BLEU33.3
17
Speech-to-text TranslationMuST-C En-X (tst-COM)
BLEU (German)22.8
16
Speech Translationlibri-trans (test)
Detokenized BLEU (case-sensitive)17.2
14
Speech TranslationMuST-C COMMON (tst)
WER (de)22.8
13
Stylized Machine TranslationMSMT en-zh Modern (test)
BLEU26.73
8
Offline Speech TranslationMuST-C v1 (test)
BLEU (DE)22.8
4
Stylized Machine TranslationMSMT zh-en Early (test)
BLEU14.28
4
Stylized Machine TranslationMSMT en-pt, Brazilian (test)
BLEU32.86
4
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Other info

Code

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