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Learning When to Commit from Partial Speech for End-to-End Simultaneous Speech Translation
Simultaneous speech translation must emit useful target text before the source is complete while preserving every committed token. We adapt a full-utterance speech language model using prefix supervision derived from its own complete- and partial-waveform translations, requiring neither transcripts
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