mlsanityData to 13 Oct 2026

NeurST: Neural Speech Translation Toolkit

arXiv 2012.10018 ↗First posted 18 Dec 2020cs.CL cs.SD eess.AScited by 23

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Abstract (arXiv)

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/.

Key facts. Cited by 23 papers in the map (data through 13 Oct 2026). First posted on arXiv 18 Dec 2020.

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Citing papers per year: 2021: 7; 2022: 6; 2023: 8; 2024: 2.

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  1. 2023Multilingual Machine Translation with Large Language Models: Empirical Results and Analysiscited by 157
  2. 2022Cross-modal Contrastive Learning for Speech Translationcited by 61
  3. 2021End-to-end Speech Translation via Cross-modal Progressive Trainingcited by 47
  4. 2021Learning When to Translate for Streaming Speechcited by 30
  5. 2022Revisiting End-to-End Speech-to-Text Translation From Scratchcited by 26
  6. 2021Searchable Hidden Intermediates for End-to-End Models of Decomposable Sequence Taskscited by 24
  7. 2023CMOT: Cross-modal Mixup via Optimal Transport for Speech Translationcited by 22
  8. 2022GigaST: A 10,000-hour Pseudo Speech Translation Corpuscited by 20
  9. 2023DUB: Discrete Unit Back-translation for Speech Translationcited by 18
  10. 2023ESPnet-ST-v2: Multipurpose Spoken Language Translation Toolkitcited by 10
  11. 2021Non-autoregressive End-to-end Speech Translation with Parallel Autoregressive Rescoringcited by 9
  12. 2021Fast-MD: Fast Multi-Decoder End-to-End Speech Translation with Non-Autoregressive Hidden Intermediatescited by 9
11 more
  1. 2023CTC-based Non-autoregressive Speech Translationcited by 9
  2. 2023End-to-End Speech-to-Text Translation: A Surveycited by 9
  3. 2022Controlling Styles in Neural Machine Translation with Activation Promptcited by 7
  4. 2024The Power of Question Translation Training in Multilingual Reasoning: Broadened Scope and Deepened Insightscited by 7
  5. 2022On the Impact of Noises in Crowd-Sourced Data for Speech Translationcited by 6
  6. 2021The Volctrans Neural Speech Translation System for IWSLT 2021cited by 3
  7. 2023Visual Information Matters for ASR Error Correctioncited by 3
  8. 2023Efficient CTC Regularization via Coarse Labels for End-to-End Speech Translationcited by 1
  9. 2024Conditioning LLMs with Emotion in Neural Machine Translationcited by 1
  10. 2021The IWSLT 2021 BUT Speech Translation Systemscited by 0
  11. 2022JoeyS2T: Minimalistic Speech-to-Text Modeling with JoeyNMTcited by 0