Estimation of word confidence using unscented transform for the rejection of misrecognized words
Jin Young Kim, Byoung Don Kim, Seung You Na · 2006
Confidence measure (CM) is generally used for the rejection of misrecognized words in automatic speech recognition (ASR). Common ASR systems test recognized words with anti-models, especially anti-phone models. That is, they calculate a word confidence with a nonlinear function, which weight nonlinearly phone-level CMs. Word confidence estimation is important in word-independent isolated word recognition, for the fixed threshold can cut out some words excessively. The statistics of word-level confidences are not consistent. In this paper we present a simple and efficient method for estimating word confidence using the unscented transform with the statistics of phone-level confidence values. Our experimental results show that the unscented transform with tri-phone-based CM statistics can estimate word confidence reasonably.