Large-scale discriminative machine translation promises to further the state-of-the-art, but has failed to deliver convincing gains over current heuristic frequency count systems.We argue that a principle reason for this failure is not dealing with multiple, equivalent translations. We present a translation model which models derivations as a latent variable, in both training and decoding, and is fully discriminative and globally optimised. Results show that accounting for multiple derivation...Expand abstract
- The Association for Computer Linguistics Publisher's website
- Publication date:
- Source identifiers:
- Local pid:
- Copyright date:
A Discriminative Latent Variable Model for Statistical Machine Translation.
If you are the owner of this record, you can report an update to it here: Report update to this record