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This paper describes our Word-level QE system for WMT 2014 shared task on Spanish-English pair. Compared to WMT 2013, this year's task is different due to the lack of SMT setting information and additional resources. We report how we overcome this challenge to retain most of the important features which performed well last year in our system. Novel features related to the availability of multiple systems output (new point of this year) are also proposed and experimented along with baseline set. The system is optimized by several ways: tuning the classification threshold, combining with WMT 2013 data, and refining using Feature Selection strategy on our development set, before dealing with the test set for submission.

LIG System for Word Level QE task at WMT14