In This paper presents an overview of a state-of-the-art text-independent speaker verification system. First, an introduction proposes a modular scheme of the training and test phases of a speaker verification system. Then, the most commonly speech parameterization used in speaker verification, namely, cepstral analysis, is detailed. Gaussian mixture modeling, which is the speaker modeling tech...

In this paper, we present a technique for bandwidth extension (BWE) of a narrowband (0 4 kHz) signal using articulatory features. The proposed technique recovers high-band components (4 8 kHz) through Gaussian mixture regression (GMR) on both the acoustic and articulatory features from the X-ray Microbeam (XRMB) speech production database. The Gaussian mixture model (GMM) that is based on acous...

The objective of this work was to investigate the segmentation ability of the Fuzzy Gaussian Mixture Models (FGMM) clustering algorithm, applied on complementary DNA (cDNA) images. A Simulated Microarray image of 200 cells, each containing one spot, was produced following standard established procedure. An automatic gridding process was developed and applied on the microarray image for the task...

Gaussian Mixture Models (GMMs) has been proposed for off-line signature verification. The individual Gaussian components are shown to represent some global features such as skewness, kurtosis, etc. that characterize various aspects of a signature, and are effective for modeling its specificity. The learning phase involves the use of Gaussian Mixture Model (GMM) technique to build a reference mo...

We propose a self-splitting Gaussian mixture learning (SGML) algorithm for Gaussian mixture modelling. The SGML algorithm is deterministic and is able to find an appropriate number of components of the Gaussian mixture model (GMM) based on a self-splitting validity measure, Bayesian information criterion (BIC). It starts with a single component in the feature space and splits adaptively during ...

Personal identity identification is an important requirement for controlling access to protected resources. Biometric identification by using certain features of a person is a more secured solution for security identification. Advances in speech processing technology and digital signal processors have made possible the design of high-performance and practical speaker recognition systems. A more...

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...

Mixture models have been widely used for data clustering. However, commonly used mixture models are generally of a parametric form (e.g., mixture of Gaussian distributions or GMM), which significantly limits their capacity in fitting diverse multidimensional data distributions encountered in practice. We propose a non-parametric mixture model (NMM) for data clustering in order to detect cluster...

This paper presents adaptive voice-quality control methods based on one-to-many eigenvoice conversion. To intuitively control the converted voice quality by manipulating a small number of control parameters, a multiple regression Gaussian mixture model (MR-GMM) has been proposed. The MR-GMM also allows us to estimate the optimum control parameters if target speech samples are available. However...

This paper describes a technique of real time head gesture recognition system. The method includes Gaussian mixture model (GMM) accompanied by optical flow algorithm which provided us the required information regarding head movement. The proposed model can be implemented in various control system. We are also presenting the result and implementation of both mentioned method.