Reading metrics for estimating task efficiency with MT output

We show that metrics derived from recording gaze while reading, are better proxies for machine translation quality than automated metrics. With reliable eyetracking technologies becoming available for home computers and mobile devices, such metrics are readily available even in the absence of representative held-out human translations. In other words, readingderived MT metrics offer a way of getting cheap, online feedback for MT system adaptation.