NeurST: Neural Speech Translation Toolkit
Chengqi Zhao, Mingxuan Wang, Qianqian Dong, Rong Ye, Lei LI
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ReproduceCode
- github.com/bytedance/neurstOfficialIn papertf★ 307
Abstract
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/.
Tasks
Benchmark Results
| Dataset | Model | Metric | Claimed | Verified | Status |
|---|---|---|---|---|---|
| libri-trans | Transformer + ASR Pretrain + SpecAug | Case-insensitive sacreBLEU | 17.2 | — | Unverified |
| libri-trans | Transformer + ASR Pretrain | Case-insensitive sacreBLEU | 16.5 | — | Unverified |
| MuST-C EN->ES | Transformer + ASR Pretrain + SpecAug | Case-sensitive sacreBLEU | 27.4 | — | Unverified |
| MuST-C EN->ES | Transformer + ASR Pretrain | Case-sensitive sacreBLEU | 26.8 | — | Unverified |
| MuST-C EN->FR | Transformer + ASR Pretrain + SpecAug | Case-sensitive sacreBLEU | 33.3 | — | Unverified |
| MuST-C EN->FR | Transformer + ASR Pretrain | Case-sensitive sacreBLEU | 32.3 | — | Unverified |