Paper: GLEU: Automatic Evaluation of Sentence-Level Fluency

ACL ID P07-1044
Title GLEU: Automatic Evaluation of Sentence-Level Fluency
Venue Annual Meeting of the Association of Computational Linguistics
Session Main Conference
Year 2007
Authors

In evaluating the output of language tech- nology applications—MT, natural language generation, summarisation—automatic eval- uation techniques generally conflate mea- surement of faithfulness to source content with fluency of the resulting text. In this paper we develop an automatic evaluation metric to estimate fluency alone, by examin- ing the use of parser outputs as metrics, and show that they correlate with human judge- ments of generated text fluency. We then de- velop a machine learner based on these, and show that this performs better than the indi- vidual parser metrics, approaching a lower bound on human performance. We finally look at different language models for gener- ating sentences, and show that while individ- ual parser metrics can be ‘fooled’ depending on genera...