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LIG System for WMT13 QE Task: Investigating the Usefulness of Features in Word Confidence Estimation for MT
Abstract : This paper presents the LIG's systems submitted for Task 2 of WMT13 Quality Estimation campaign. This is a word confidence estimation (WCE) task where each participant was asked to label each word in a translated text as a binary (Keep/Change) or multi-class (Keep/Substitute/Delete) category. We integrate a number of features of various types (system-based, lexical, syntactic and semantic) into the conventional feature set, for our baseline classifier training. After the experiments with all features, we deploy a " Feature Selection " strategy to keep only the best performing ones. Then, a method that combines multiple " weak " classifiers to build a strong " composite " classifier by taking advantage of their complementarity is presented and experimented. We then select the best systems for submission and present the official results obtained.
Cited literature [12 references]
https://hal.archives-ouvertes.fr/hal-00953773
Contributor : Laurent Besacier Connect in order to contact the contributor
Submitted on : Thursday, November 23, 2017 - 11:51:06 AM
Last modification on : Thursday, October 21, 2021 - 3:51:27 AM
Contributor : Laurent Besacier Connect in order to contact the contributor
Submitted on : Thursday, November 23, 2017 - 11:51:06 AM
Last modification on : Thursday, October 21, 2021 - 3:51:27 AM
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LIGSystemForWMT13_ok.pdf
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