Confidence estimation for NLP applications

Authors:
Simona Gandrabur;George Foster;Guy Lapalme
Affiliations:
RALI, Université de Montréal, Montréal, Québec, Canada;National Research Council, Gatineau, Quebec, Canada;RALI, Université de Montréal, Montréal, Québec, Canada
Venue:
ACM Transactions on Speech and Language Processing (TSLP)
Year:
2006

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Abstract

Confidence measures are a practical solution for improving the usefulness of Natural Language Processing applications. Confidence estimation is a generic machine learning approach for deriving confidence measures. We give an overview of the application of confidence estimation in various fields of Natural Language Processing, and present experimental results for speech recognition, spoken language understanding, and statistical machine translation.