Anticipation-Free Training for Simultaneous Machine Translation. (arXiv:2201.12868v2 [cs.CL] UPDATED)

Simultaneous machine translation (SimulMT) speeds up the translation process
by starting to translate before the source sentence is completely available. It
is difficult due to limited context and word order difference between
languages. Existing methods increase latency or introduce adaptive read-write
policies for SimulMT models to handle local reordering and improve translation
quality. However, the long-distance reordering would make the SimulMT models
learn translation mistakenly. Specifically, the model may be forced to predict
target tokens when the corresponding source tokens …

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