Word level confidence measurement using semantic features
Ruhi Sarikaya, Yuqing Gao, Michael Picheny · 2003 IEEE International Conference on Acoustics, Speech, and Signal Processing, 2003. Proceedings. (ICASSP '03). · 2003
This paper proposes two principled methods to incorporate semantic information into word level confidence measurement. The first technique uses tag and arc probabilities obtained from a statistical classer and parser tree. The second technique uses a maximum entropy based semantic structured language model to use semantic structure of a sentence to assign semantic probabilities to each word. Semantic features provide significant improvements over a posterior probability based confidence measure when used together in an air travel reservation task.