This research investigates the use of utterance-level features for confidence scoring. Confidence scores are used to accept or reject user utterances in our conversational weather information system. We have developed an automatic labeling algorithm based on a semantic frame comparison between recognized and transcribed orthographies. We explore recognition-based features along with semantic, linguistic, and application-specific features for utterance rejection. Discriminant analysis is used in an iterative process to select the best set of classification features for our utterance rejection sub-system. Experiments show that we can correctly reject over 60% of incorrectly understood utterances while accepting 98% of all correctly understood utterances.
Cite as: Pao, C., Schmid, P., Glass, J.R. (1998) Confidence scoring for speech understanding systems. Proc. 5th International Conference on Spoken Language Processing (ICSLP 1998), paper 0392, doi: 10.21437/ICSLP.1998-430
@inproceedings{pao98_icslp,
author={Christine Pao and Philipp Schmid and James R. Glass},
title={{Confidence scoring for speech understanding systems}},
year=1998,
booktitle={Proc. 5th International Conference on Spoken Language Processing (ICSLP 1998)},
pages={paper 0392},
doi={10.21437/ICSLP.1998-430}
}