Semantic Confidence Measurement for Spoken Dialogue Systems (2005)
| Venue: | IEEE Trans. on SAP |
| Citations: | 5 - 0 self |
BibTeX
@ARTICLE{Sarikaya05semanticconfidence,
author = {Ruhi Sarikaya and Yuqing Gao and Michael Picheny and Hakan Erdogan},
title = {Semantic Confidence Measurement for Spoken Dialogue Systems},
journal = {IEEE Trans. on SAP},
year = {2005},
volume = {13},
pages = {534--545}
}
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Abstract
Abstract—This paper proposes two methods to incorporate semantic information into word and concept level confidence measurement. The first method uses tag and extension probabilities obtained from a statistical classer and parser. The second method uses a maximum entropy based semantic structured language model to assign probabilities to each word. Incorporation of semantic features into a lattice posterior probability based confidence measure provides significant improvements compared to posterior probability when used together in an air travel reservation task. At 5% False Alarm (FA) rate relative improvements of 28 % and 61 % in Correct Acceptance (CA) rate are achieved for word level and concept level confidence measurements, respectively. I.
