Paper: Don’t Until the Final Verb Wait: Reinforcement Learning for Simultaneous Machine Translation

ACL ID D14-1140
Title Don’t Until the Final Verb Wait: Reinforcement Learning for Simultaneous Machine Translation
Venue Conference on Empirical Methods in Natural Language Processing
Session Main Conference
Year 2014
Authors

We introduce a reinforcement learning- based approach to simultaneous ma- chine translation?producing a trans- lation while receiving input words? between languages with drastically dif- ferent word orders: from verb-final lan- guages (e.g., German) to verb-medial languages (English). In traditional ma- chine translation, a translator must ?wait? for source material to appear be- fore translation begins. We remove this bottleneck by predicting the final verb in advance. We use reinforcement learn- ing to learn when to trust predictions about unseen, future portions of the sentence. We also introduce an evalua- tion metric to measure expeditiousness and quality. We show that our new translation model outperforms batch and monotone translation strategies.