Thinking Slow about Latency Evaluation for Simultaneous Machine Translation

05/31/2019
by   Colin Cherry, et al.
0

Simultaneous machine translation attempts to translate a source sentence before it is finished being spoken, with applications to translation of spoken language for live streaming and conversation. Since simultaneous systems trade quality to reduce latency, having an effective and interpretable latency metric is crucial. We introduce a variant of the recently proposed Average Lagging (AL) metric, which we call Differentiable Average Lagging (DAL). It distinguishes itself by being differentiable and internally consistent to its underlying mathematical model.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
04/18/2021

Stream-level Latency Evaluation for Simultaneous Machine Translation

Simultaneous machine translation has recently gained traction thanks to ...
research
06/12/2019

Monotonic Infinite Lookback Attention for Simultaneous Machine Translation

Simultaneous machine translation begins to translate each source sentenc...
research
05/10/2018

Automatic Estimation of Simultaneous Interpreter Performance

Simultaneous interpretation, translation of the spoken word in real-time...
research
04/07/2020

Re-translation versus Streaming for Simultaneous Translation

There has been great progress in improving streaming machine translation...
research
06/12/2022

Over-Generation Cannot Be Rewarded: Length-Adaptive Average Lagging for Simultaneous Speech Translation

Simultaneous speech translation (SimulST) systems aim at generating thei...
research
03/04/2022

From Simultaneous to Streaming Machine Translation by Leveraging Streaming History

Simultaneous Machine Translation is the task of incrementally translatin...
research
05/18/2020

Efficient Wait-k Models for Simultaneous Machine Translation

Simultaneous machine translation consists in starting output generation ...

Please sign up or login with your details

Forgot password? Click here to reset