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 ICASSP 2020 - 2020 IEEE International Conference on Acous- tics, Speech and Signal Processing (ICASSP) , pages 6074–6078
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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.