Automatic evaluation of sentence fluency
Ding Liu, Yu Zhou, Chengqing Zong, Fuji Ren · 2004
In the machine translation (MT) system, how to evaluate the sentence fluency of the translation results is an important research topic. Most of the current methods are based on the similarity of output words compared with the reference translations, which don't specially address the evaluation of the sentence fluency according to the syntactic structure. This paper proposes a statistical approach to the problem, which is based on the n-gram language model and reference-independent. Our approach is a beneficial compensation to the reference-dependent methods and has better robustness than those methods based on the syntactic analysis. The preliminary experimental results indicate that the approach basically reflects the reality of human's judgment.