| Paper: | SLP-P19.10 | ||
| Session: | Model-based Robust Speech Recognition | ||
| Time: | Friday, May 19, 10:00 - 12:00 | ||
| Presentation: | Poster | ||
| Topic: | Speech and Spoken Language Processing: Confidence Measures and Rejection algorithms | ||
| Title: | Compensating for Word Posterior Estimation Bias in Confusion Networks | ||
| Authors: | Dustin Hillard, Mari Ostendorf, University of Washington, United States | ||
| Abstract: | 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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