What does it take to get state of the art in simultaneous speech-to-speech translation?

Vincent Wilmet, Johnson Du
9/2/2024
cs.CL

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Abstract

This paper presents an in-depth analysis of the latency characteristics observed in simultaneous speech-to-speech model's performance, particularly focusing on hallucination-induced latency spikes. By systematically experimenting with various input parameters and conditions, we propose methods to minimize latency spikes and improve overall performance. The findings suggest that a combination of careful input management and strategic parameter adjustments can significantly enhance speech-to-speech model's latency behavior.

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Cite this paper

@article{wilmet2024what,
  title  = {What does it take to get state of the art in simultaneous speech-to-speech translation?},
  author = {Vincent Wilmet and Johnson Du},
  year   = {2024},
  eprint = {2409.00965},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2409.00965v2}
}

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