Evaluating the Learning Curve of Domain Adaptive Statistical Machine Translation Systems

The new frontier of computer assisted translation technology is the effective integration of statistical MT within the translation workflow. In this respect, the SMT ability of incrementally learning from the translations produced by users plays a central role. A still open problem is the evaluation of SMT systems that evolve over time. In this paper, we propose a new metric for assessing the quality of an adaptive MT component that is derived from the theory of learning curves: the percentage slope.