mlsanityData to 14 Oct 2026

IMS' Systems for the IWSLT 2021 Low-Resource Speech Translation Task

arXiv 2106.16055 ↗First posted 30 Jun 2021cs.CL cs.SD eess.AScited by 3

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Abstract (arXiv)

This paper describes the submission to the IWSLT 2021 Low-Resource Speech Translation Shared Task by IMS team. We utilize state-of-the-art models combined with several data augmentation, multi-task and transfer learning approaches for the automatic speech recognition (ASR) and machine translation (MT) steps of our cascaded system. Moreover, we also explore the feasibility of a full end-to-end speech translation (ST) model in the case of very constrained amount of ground truth labeled data. Our best system achieves the best performance among all submitted systems for Congolese Swahili to English and French with BLEU scores 7.7 and 13.7 respectively, and the second best result for Coastal Swahili to English with BLEU score 14.9.

Key facts. Cited by 3 papers in the map (data through 14 Oct 2026). Builds on 19 of its 31 references that are in the map. First posted on arXiv 30 Jun 2021.

Builds on

19 of 31 references.

References · 19

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7 more
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Cited by year

Citing papers per year: 2022: 2; 2023: 0; 2024: 1.

3 papers.

  1. 2022ArzEn-ST: A Three-way Speech Translation Corpus for Code-Switched Egyptian Arabic - Englishcited by 13
  2. 2022Investigating Lexical Replacements for Arabic-English Code-Switched Data Augmentationcited by 9
  3. 2024ArzEn-LLM: Code-Switched Egyptian Arabic-English Translation and Speech Recognition Using LLMscited by 3