Post-Editing of machine translation outputs requires considerable effort and expense. It is also difficult to predict the time required to post-edit a translation and bring it up to publishable translation quality. A method was developed to help in predicting this post-editing effort and this is called Translation Error Rate(TER).
TER is quick to use, inexpensive to operate, language independent and correlates highly with actual post-editing effort. The lower the score the better!
TER measures the amount of editing that a translator would have to perform to change a translation so it exactly matches a reference translation. By repeating this analysis on a large number of sample translations, it is possible to estimate the post-editing effort required for a project.
A TER score is a value in the range of 0-1, but is frequently presented as a percentage, where lower is better. A high TER score suggests that a translation will require more post-editing.