Paper: Confidence Estimation For Translation Prediction

ACL ID W03-0413
Title Confidence Estimation For Translation Prediction
Venue International Conference on Computational Natural Language Learning
Session Main Conference
Year 2003

The purpose of this work is to investigate the use of machine learning approaches for confi- dence estimation within a statistical machine translation application. Specifically, we at- tempt to learn probabilities of correctness for various model predictions, based on the native probabilites (i.e. the probabilites given by the original model) and on features of the current context. Our experiments were conducted us- ing three original translation models and two types of neural nets (single-layer and multi- layer perceptrons) for the confidence estima- tion task.