WMDO: Fluency-based Word Mover’s Distance for Machine Translation Evaluation
Julian Chow, Lucia Specia, Pranava Madhyastha · 2019
We propose WMD O , a metric based on distance between distributions in the semantic vector space.Matching in the semantic space has been investigated for translation evaluation, but the constraints of a translation's word order have not been fully explored.Building on the Word Mover's Distance metric and various word embeddings, we introduce a fragmentation penalty to account for fluency of a translation.This word order extension is shown to perform better than standard WMD, with promising results against other types of metrics.