A survey of 110 SimulST papers shows most systems rely on unrealistic human pre-segmented audio and inconsistent terminology, and it offers a taxonomy and recommendations to fix both.
In Proceedings of the 21st International Conference on Spoken Lan- guage Translation (IWSLT 2024) , pages 170– 182, Bangkok, Thailand (in-person and online)
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How "Real" is Your Real-Time Simultaneous Speech-to-Text Translation System?
A survey of 110 SimulST papers shows most systems rely on unrealistic human pre-segmented audio and inconsistent terminology, and it offers a taxonomy and recommendations to fix both.