When to Speak: Training Translation Models to Know What Is Safe to Commit
TL;DR for operators A simultaneous translator repeatedly has to decide whether to emit another target token now or wait for more source context. Hoang and Axelrod show that this decision can be improved by training the translation model on examples that explicitly encode how much of a partial translation has already become consistent with the model’s eventual full-sentence output.1 ...