Abstract: A method of estimating a confidence measure for a speech recognition system, involves comparing an input speech signal with a number of predetermined models of possible speech signals. Best scores indicating the degree of similarity between the input speech signal and each of the predetermined models are then used to determine a normalized variance, which is used as the Confidence Measure, in order to determine whether the input speech signal has been correctly recognized, the Confidence Measure is compared to a threshold value. The threshold value is weighted according to the Signal to Noise Ratio of the input speech signal and according to the number of predetermined models used.

Abstract: An apparatus for selecting a cohort model for use in a speaker verification system includes a model generator (108) for determining a target speaker model (114) from a speech sample collected from the target speaker (106). A cohort selector (110) determines a similarity value between each of a number of predetermined existing speaker models from a model pool (112) and the target speaker model (114) and a dissimilarity value between each of the existing speaker models and any previously selected cohort models (116). An existing speaker model which is most similar to the target speaker model, but most dissimilar to previously chosen cohort models, is then chosen as another cohort model for the target speaker.