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 62nd Annual Meeting of the Association for Compu- tational Linguistics (Volume 1: Long Papers) , pages 1557–1575, Bangkok, Thailand
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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.