# How to compute classification accuracy for machine translation?

I looked online and am unable to find the proper classification metric for machine translation problems.

Let's the predicted output is: "My name John" and the ground truth is "My name is John"

I know I can compute word error rate (which is computed using edit distance). And if the number of words are the same, then classification error is simply equal to word error rate. Then classification accuracy is simply 1 minus classification accuracy.

But how do I compute classification error when the number of words are different like in my above example?

• There are many standard metrics for evaluating machine translation systems. Start by searching for BLEU and ROUGE. Jun 2 '20 at 1:06