title   
  

Filler model based confidence measures for spoken dialogue systems: a case study for Turkish

Akyol, Aydın and Erdoğan, Hakan (2004) Filler model based confidence measures for spoken dialogue systems: a case study for Turkish. In: IEEE International Conference on Acoustics, Speech, and Signal Processing, 2004 (ICASSP '04), Montreal, Quebec, Canada

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Official URL: http://dx.doi.org/10.1109/ICASSP.2004.1326102

Abstract

Because of the inadequate performance of speech recognition systems, an accurate confidence scoring mechanism should be employed to understand user requests correctly. To determine a confidence score for a hypothesis, certain confidence features are combined. The performance of filler-model based confidence features have been investigated. Five types of filler model networks were defined: triphone-network; phone-network; phone-class network; 5-state catch-all model; 3-state catch-all model. First, all models were evaluated in a Turkish speech recognition task in terms of their ability to tag correctly (recognition-error or correct) recognition hypotheses. The best performance was obtained from the triphone recognition network. Then, the performances of reliable combinations of these models were investigated and it was observed that certain combinations of filler models could significantly improve the accuracy of the confidence annotation

Item Type:Papers in Conference Proceedings
Subjects:UNSPECIFIED
ID Code:11459
Deposited By:Hakan Erdoğan
Deposited On:13 Apr 2009 09:49
Last Modified:25 May 2011 14:23

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