English

Improving Stability in Simultaneous Speech Translation: A Revision-Controllable Decoding Approach

Computation and Language 2023-10-09 v1

Abstract

Simultaneous Speech-to-Text translation serves a critical role in real-time crosslingual communication. Despite the advancements in recent years, challenges remain in achieving stability in the translation process, a concern primarily manifested in the flickering of partial results. In this paper, we propose a novel revision-controllable method designed to address this issue. Our method introduces an allowed revision window within the beam search pruning process to screen out candidate translations likely to cause extensive revisions, leading to a substantial reduction in flickering and, crucially, providing the capability to completely eliminate flickering. The experiments demonstrate the proposed method can significantly improve the decoding stability without compromising substantially on the translation quality.

Keywords

Cite

@article{arxiv.2310.04399,
  title  = {Improving Stability in Simultaneous Speech Translation: A Revision-Controllable Decoding Approach},
  author = {Junkun Chen and Jian Xue and Peidong Wang and Jing Pan and Jinyu Li},
  journal= {arXiv preprint arXiv:2310.04399},
  year   = {2023}
}

Comments

accepted by ASRU 2023

R2 v1 2026-06-28T12:42:48.065Z