Leveraging Synthetic Audio Data for End-to-End Low-Resource Speech Translation

Yasmin Moslem
6/25/2024
cs.CLcs.SDeess.AS

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Abstract

This paper describes our system submission to the International Conference on Spoken Language Translation (IWSLT 2024) for Irish-to-English speech translation. We built end-to-end systems based on Whisper, and employed a number of data augmentation techniques, such as speech back-translation and noise augmentation. We investigate the effect of using synthetic audio data and discuss several methods for enriching signal diversity.

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Cite this paper

@article{moslem2024leveraging,
  title  = {Leveraging Synthetic Audio Data for End-to-End Low-Resource Speech Translation},
  author = {Yasmin Moslem},
  year   = {2024},
  eprint = {2406.17363},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2406.17363v2}
}

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