Paper: Multi-Metric Optimization Using Ensemble Tuning

ACL ID N13-1115
Title Multi-Metric Optimization Using Ensemble Tuning
Venue Annual Conference of the North American Chapter of the Association for Computational Linguistics
Session Main Conference
Year 2013

This paper examines tuning for statistical ma- chine translation (SMT) with respect to mul- tiple evaluation metrics. We propose several novel methods for tuning towards multiple ob- jectives, including some based on ensemble decoding methods. Pareto-optimality is a nat- ural way to think about multi-metric optimiza- tion (MMO) and our methods can effectively combine several Pareto-optimal solutions, ob- viating the need to choose one. Our best performing ensemble tuning method is a new algorithm for multi-metric optimization that searches for Pareto-optimal ensemble models. We study the effectiveness of our methods through experiments on multiple as well as single reference(s) datasets. Our experiments show simultaneous gains across several met- rics (BLEU, RIBES), without any significant...