Application of prize based on sentence length in chunk-based automatic evaluation of machine translation

Abstract

As described in this paper, we propose a new automatic evaluation metric for machine translation. Our metric is based on chunking between the reference and candidate translation. Moreover, we apply a prize based on sentence-length to the metric, dissimilar from penalties in BLEU or NIST. We designate this metric as Automatic Evaluation of Machine Translation in which the Prize is Applied to a Chunkbased metric (APAC). Through metaevaluation experiments and comparison with several metrics, we confirmed that our metric shows stable correlation with human judgment.