In this paper we describe two new confidence measures for estimating the reliability of speech-to-text output: "Likelihood Dependence" and "Neighborhood Dependence". Each word in the speech-to-text output for a given utterance is annotated with these two measures. Likelihood dependence for a given word occurrence indicates how critical that word is to the overall utterance likelihood; i.e., how much worse is the likelihood of the next best utterance if that word is eliminated from the recognition. Neighborhood dependence measures how stable a given word is when neighboring words are changed in the recognition. We show that correct and incorrect words in the recognition behave significantly differently with respect to these measures. We also show that on the broadcast news task they perform better than some of the existing, commonly used measures.
Cite as: Bansal, D., Ravishankar, M.K. (1998) New features for confidence annotation. Proc. 5th International Conference on Spoken Language Processing (ICSLP 1998), paper 0829, doi: 10.21437/ICSLP.1998-639
@inproceedings{bansal98_icslp,
author={Dhananjay Bansal and Mosur K. Ravishankar},
title={{New features for confidence annotation}},
year=1998,
booktitle={Proc. 5th International Conference on Spoken Language Processing (ICSLP 1998)},
pages={paper 0829},
doi={10.21437/ICSLP.1998-639}
}