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Semantic confidence measurement for spoken dialog systems

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4 Author(s)
Sarikaya, R. ; Human Language Technol. Group, IBM T.J. Watson Res. Center, Yorktown Heights, NY, USA ; Yuqing Gao ; Picheny, Michael ; Erdogan, Hakan

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.

Published in:

Speech and Audio Processing, IEEE Transactions on  (Volume:13 ,  Issue: 4 )

Date of Publication:

July 2005

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