In conventional Speaker-Identification using GMM-UBM framework, the likelihood of the given test utterance is computed with respect to all speaker-models before identifying the speaker, based on the maximum likelihood criterion. The calculation of likelihood score of the test utterance is computationally intensive, especially when there are tens of thousands of speakers in database. In this pap...

diagnosis of corneal diseases is possible by measuring and evaluation of corneal thickness in different layers. thus, the need for precise segmentation of corneal layer boundaries is inevitable. obviously, manual segmentation is time‑consuming and imprecise. in this paper, the gaussian mixture model (gmm) is used for automatic segmentation of three clinically important corneal boundaries on opt...

In this paper we introduce a new chaotic system and its corresponding circuit. This system has a special property of having a hidden attractor. Systems with hidden attractors are newly introduced and barely investigated. Conventional methods for parameter estimation in models of these systems have some limitations caused by sensitivity to initial conditions. We use a geometry based cost functio...

Comfort noise insertion during speech pause has been applied to Voice-over-IP and wireless networks for increasing bandwidth efficiency. We present two classified comfort noise generation (CCNG) schemes using Gaussian Mixture classifiers (GMM-C). Our first scheme employs a classified prototype background noise codebook with the prototype noise waveform chosen using a GMM-C. The second scheme ut...

This paper analyzes the higher order asymptotic properties of Generalized Method of Moments (GMM) estimators for linear time series models using many lags as instruments. A data dependent moment selection method based on minimizing the approximate mean squared error is developed. In addition, a new version of the GMM estimator based on kernel weighted moment conditions is proposed. It is shown ...

We compare the performance of ve algorithms for vector quan-tisation and clustering analysis: the Self-Organising Map (SOM) and Learning Vector Quantization (LVQ) algorithms of Kohonen, the Linde-Buzo-Gray (LBG) algorithm, the MultiLayer Perceptron (MLP) and the GMM/EM algorithm for Gaussian Mixture Models (GMM). We propose that the GMM/EM provides a better representation of the speech space an...

In tradition probability statistics model, speaker verification threshold is instability in different test situations. A novel speaker verification method based on Support Vector Data Description (SVDD) is proposed to remedy the defect of probability statistics model. To simplify the threshold value setting and improve the robustness and recognition accuracy of the verification system, traditio...