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Compensating for Word Posterior Estimation Bias in Confusion Networks Export

Acoustics, Speech and Signal Processing, 2006. ICASSP 2006 Proceedings. 2006 IEEE International Conference on In Acoustics, Speech and Signal Processing, 2006. ICASSP 2006 Proceedings. 2006 IEEE International Conference on, Vol. 1 (2006), pp. I-I.

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confidence confusion network

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This paper looks at the problem of confidence estimation at the word network level, where multiple hypotheses from a recognizer are represented in a confusion network. Given features of the network, an SVM is used to estimate the probability that the correct word is missing from a candidate slot and then other word probabilities are normalized accordingly. The result is a reduction in overall bias of the estimated word posteriors and an improvement in the confidence estimate for the top word hypothesis in particular


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