Compensating for Word Posterior Estimation Bias in Confusion Networks
Hillard, D.; Ostendorf, M.
Acoustics, Speech and Signal Processing, 2006. ICASSP 2006 Proceedings. 2006 IEEE International Conference on
Volume 1, Issue , 14-19 May 2006 Page(s):I - I
Digital Object Identifier   10.1109/ICASSP.2006.1660230
Summary: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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