Dynamic Lagging using Stable-Prefix Training for Simultaneous Translation
In streaming simultaneous speech translation, the speech translation system is trained to learn a read-write policy that alternates between consuming source words and generating target ones. In a cascaded setting, the output from the speech recognizer is passed to a separate machine translation component, making it more difficult to learn such a policy. Approximations such as fixed wait-k strategies or target-suffix deletion can be employed, but these approaches do not provide the model with a streaming system's flexibility to make contextual read-write decisions. This paper presents a training strategy for a cascaded machine translation system that enables it to dynamically decide how mu...
| Authors | Hieu Hoang, Amittai Axelrod, Matt Post |
|---|---|
| Primary category | cs.CL |
| Published | 5 September 2026 |
| Last updated at source | 17 September 2026 |
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