Confidence measures for hybrid HMM/ANN speech recognition
Gethin Williams, Steve J. Renals · 1997
In this paper we introduce four acoustic confidence measures which are derived from the output of a hybrid HMM/ANN large vocabulary continuous speech recognition system. These confidence measures, based on local posterior probability estimates computed by an ANN, are evaluated at both phone and word levels, using the North American Business News corpus. 1. INTRODUCTION A reliable measure of the confidence of a speech recogniser's output is useful in many circumstances. A word may be hypothesised with low confidence when an out-of-vocabulary (OOV) word is encountered or when the word model is matched against unclear acoustics caused by disfluencies or noise. Both OOV words and unclear acoustics are a major source of recogniser error. A confidence measure based on can be used to reject those hypotheses which are likely to be erroneous (i.e., have a low confidence) in a hypothesis test. Additionally, a reliable confidence measure may be of practical use in recognition search (confidence ...