ILR-Based MT Comprehension Test with Multi-Level Questions

We present results from a new Interagency Language Roundtable (ILR) based comprehension test. This new test design presents questions at multiple ILR difficulty levels within each document. We incorporated Arabic machine translation (MT) output from three independent research sites, arbitrarily merging these materials into one MT condition. We contrast the MT condition, for both text and audio data types, with high quality human reference Gold Standard (GS) translations. Overall, subjects achieved 95% comprehension for GS and 74% for MT, across all genres and difficulty levels. Interestingly, comprehension rates do not correlate highly with translation error rates, suggesting that we are measuring an additional dimension of MT quality.

• Type: Conference
• Year: 2007
• Where: NAACL
• Authors: Douglas Jones, Martha Herzog, Hussny Ibrahim, Arvind Jairam, Wade Shen, Edward Gibson, Michael Emonts
• Keywords: Computational Linguistics, Difficulty Levels, ILR Difficulty Levels, MT Condition, NAACL 2007