ELITR Non-Native Speech Translation at IWSLT 2020
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Abstract (arXiv)
This paper is an ELITR system submission for the non-native speech translation task at IWSLT 2020. We describe systems for offline ASR, real-time ASR, and our cascaded approach to offline SLT and real-time SLT. We select our primary candidates from a pool of pre-existing systems, develop a new end-to-end general ASR system, and a hybrid ASR trained on non-native speech. The provided small validation set prevents us from carrying out a complex validation, but we submit all the unselected candidates for contrastive evaluation on the test set.
Key facts. Cited by 5 papers in the map (data through 7 Oct 2026). First posted on arXiv 5 Jun 2020.
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Citing papers per year: 2021: 4; 2022: 0; 2023: 0; 2024: 1.
5 papers.
- 2021AuGPT: Auxiliary Tasks and Data Augmentation for End-To-End Dialogue with Pre-Trained Language Modelscited by 31
- 2024How "Real" is Your Real-Time Simultaneous Speech-to-Text Translation System?cited by 17
- 2021Variational Latent-State GPT for Semi-Supervised Task-Oriented Dialog Systemscited by 13
- 2021Backtranslation Feedback Improves User Confidence in MT, Not Qualitycited by 10
- 2021Lost in Interpreting: Speech Translation from Source or Interpreter?cited by 10
- 2024How "Real" is Your Real-Time Simultaneous Speech-to-Text Translation System?24 Dec 2024
- 2021Variational Latent-State GPT for Semi-Supervised Task-Oriented Dialog Systems9 Sep 2021
- 2021Lost in Interpreting: Speech Translation from Source or Interpreter?17 Jun 2021
- 2021Backtranslation Feedback Improves User Confidence in MT, Not Quality12 Apr 2021
- 2021AuGPT: Auxiliary Tasks and Data Augmentation for End-To-End Dialogue with Pre-Trained Language Models9 Feb 2021