Papers › NeurST: Neural Speech Translation Toolkit
NeurST: Neural Speech Translation Toolkit
Chengqi Zhao, Mingxuan Wang, Qianqian Dong, Rong Ye, Lei LI
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/.
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Code
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Tasks
Results from the paper archive 2025-07-28
| Task | Dataset | Model | Metric | Value | Rank at snapshot | Leaderboard | Report |
|---|---|---|---|---|---|---|---|
| Speech-to-Text Translation | MuST-C EN->DE | Transformer + ASR Pretrain | Case-sensitive sacreBLEU | 22.8 | #7 of 8 | Archive leaderboard | report |
| Speech-to-Text Translation | MuST-C EN->ES | Transformer + ASR Pretrain + SpecAug | Case-sensitive sacreBLEU | 27.4 | #4 of 5 | Archive leaderboard | report |
| Speech-to-Text Translation | MuST-C EN->ES | Transformer + ASR Pretrain | Case-sensitive sacreBLEU | 26.8 | #5 of 5 | Archive leaderboard | report |
| Speech-to-Text Translation | MuST-C EN->FR | Transformer + ASR Pretrain + SpecAug | Case-sensitive sacreBLEU | 33.3 | #2 of 3 | Archive leaderboard | report |
| Speech-to-Text Translation | MuST-C EN->FR | Transformer + ASR Pretrain | Case-sensitive sacreBLEU | 32.3 | #3 of 3 | Archive leaderboard | report |
| Speech-to-Text Translation | libri-trans | Transformer + ASR Pretrain + SpecAug | Case-insensitive sacreBLEU | 17.2 | #1 of 2 | Archive leaderboard | report |
| Speech-to-Text Translation | libri-trans | Transformer + ASR Pretrain + SpecAug | Case-insensitive tokenized BLEU | 18.7 | #1 of 2 | Archive leaderboard | report |
| Speech-to-Text Translation | libri-trans | Transformer + ASR Pretrain + SpecAug | Case-sensitive sacreBLEU | 16.3 | #1 of 2 | Archive leaderboard | report |
| Speech-to-Text Translation | libri-trans | Transformer + ASR Pretrain + SpecAug | Case-sensitive tokenized BLEU | 17.8 | #1 of 2 | Archive leaderboard | report |
| Speech-to-Text Translation | libri-trans | Transformer + ASR Pretrain | Case-insensitive sacreBLEU | 16.5 | #2 of 2 | Archive leaderboard | report |
| Speech-to-Text Translation | libri-trans | Transformer + ASR Pretrain | Case-insensitive tokenized BLEU | 17.9 | #2 of 2 | Archive leaderboard | report |
| Speech-to-Text Translation | libri-trans | Transformer + ASR Pretrain | Case-sensitive sacreBLEU | 15.5 | #2 of 2 | Archive leaderboard | report |
| Speech-to-Text Translation | libri-trans | Transformer + ASR Pretrain | Case-sensitive tokenized BLEU | 16.9 | #2 of 2 | Archive leaderboard | report |
Ranks are positions in the archive's leaderboards as they stood at the 2025-07-28 snapshot. Results published since then are not among these rows, so a rank here is not a current standing.
Methods
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