Modelling output probability distributions for enhancing speaker recognition
نویسندگان
چکیده
This paper discusses the use of a secondary likelihood classifier scheme for improving speaker recognition performance. The system models the output likelihoods of a typical Gaussian Mixture Model system across multiple speakers. The Output Probability Distributions (OPD) of the primary classifiers contain information on inter-speaker relationships, and are modelled by secondary classifiers to improve recognition accuracies. A comparison of the OPD system with the traditional likelihood ratio and maximum likelihood scoring schemes for verification and identification is performed. Fusion of traditional measures with OPDs is shown to enhance overall recognition performance.
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