MT Evaluation in General

Lecture 4: General MT Evaluation

Lecture video:	web TODO Youtube

{{#ev:youtube|_QL-BUxIIhU|800|center}}

Data Splits

Available training data is usually split into several parts, e.g. training, development (held-out) and (dev-)test. Training data is used to estimate model parameters, development set can be used for model selection, hyperparameter tuning etc. and dev-test is used for continuous evaluation of progress (are we doing better than before?).

However, you should always keep an additional (final) test set which is used only very rarely. Evaluating your system on the final test set can then be used as a rough estimate of its true performance because you do not use it in the development process at all, and therefore do not bias your system towards it.

The "golden rule" of (MT) evaluation: Evaluate on unseen data!

Example Sentence + Translations

Original German sentence:

   Arbeiter sturzte von Leiter: schwer verletzt

English reference translation:

   Worker falls from ladder: seriously injured

MT Output	Notes
Workers rushed from director: Seriously injured	plural (workers), bad choice of verb (rushed), Leiter mistranslated as director
Workers fell from ladder: hurt	plural (workers), intensifier missing
Worker rushed from ladder: schwer verletzt	bad choice of verb (rushed), tail is left untranslated
Worker fell from leader: heavily injures	Leiter translated as leader (not a typo, a bad lexical choice), poor morphological choices