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ILR-based MT comprehension test with multi-level questions

Authors :
Edward Gibson
Michael Emonts
Douglas L. Jones
Martha Herzog
Arvind Jairam
Wade Shen
Hussny Ibrahim
Source :
HLT-NAACL (Short Papers)
Publication Year :
2007
Publisher :
Association for Computational Linguistics, 2007.

Abstract

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 4 genres and 3 difficulty levels. Surprisingly, comprehension rates do not correlate highly with translation error rates, suggesting that we are measuring an additional dimension of MT quality. We observed that it takes 15% more time overall to read MT than GS.

Details

Database :
OpenAIRE
Journal :
Human Language Technologies 2007: The Conference of the North American Chapter of the Association for Computational Linguistics; Companion Volume, Short Papers on XX - NAACL '07
Accession number :
edsair.doi...........28cb1fcc45d32fc93c91b57f4716e466
Full Text :
https://doi.org/10.3115/1614108.1614128