... Abstract- Speaker recognition is a term which is most popular in biometric recognition technique that tends to identify and verify a speaker from his/her speech data. Speaker recognition system uses mechanism to ...

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... A **mixture** **model** has been explain by assuming that every observed data point had a corresponding unobserved data point, or latent variable, specifying **mixture** component that each data point belongs ...

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... Abstract. This paper proposes a novel piecewise linear optimal compander design method based on the mean- square approximation of the first derivative of the optimal compressor function. Designing of the piecewise linear ...

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... Truncated **Gaussian** **Mixture** ...Truncated **Gaussian** **mixture** are generated, the test signal is considered and the PDF values of the test signals are classified to ascertain the ...

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... namely **Gaussian** **mixture** **model**, k-means and two algo- rithms of discriminant functions including QDF, in order to distinguish microearthquakes from quarry blasts in the vicin- ity of ...

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... Abstract---This chapter describes a method of segmenting MR images into different tissue classes, using a modified **Gaussian** **Mixture** **Model**. By knowing the prior spatial probability of each voxel being ...

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... basic **model**, yielding fairly good initial ...a **Gaussian** **mixture** **model** (EMGMM) using information from the analysis of phantom ...a **Gaussian** MRF, using Gibbs distri- butions to obtain the ...

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... The projected work intense only in finding the outflow of blood from the Mitral Valve (MV) and is generally called as Mitral Regurgitation (MR). Through the echocardiographic video, the outflow is traced and segmented. ...

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... In this article, we propose a new feature which could be used for the framework of SVM-based language recognition, by introducing the idea of total variability used in speaker recognition to language recognition. We ...

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... the **Gaussian** **Mixture** **Model** (GMM) is the mostly used **model** due to its robustness to various challenges and good computation and memory ...requirements. **Gaussian** basically is a ...

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... Segmentation of multi-temporal images is done using curvelet transformation & **Gaussian** **Mixture** **Model** (GMM). A comparison study has been made between the accuracy values of segmentation ...

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... of **Gaussian** **mixture** **model** (GMM) states that due to the influence of environmental factors, the gray value of each pixel in the video image will change with the ...multiple **Gaussian** ...

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... using **Gaussian** **mixture** **model** (GMM) with spatial information is ...Thirdly, **Gaussian** **Mixture** **Model** is used for segmentation of the difference image in which the parameters are ...

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... Generalized **Gaussian** **Mixture** **Model** The Features obtained from the finger prints are considered and the Probability Density Function is calculated, This PDF is matched with that of the existing ...

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... A visual traffic surveillance application oriented, probabilistic approach based large scale moving objects strategy has been presented in this paper. The modified proposal of an unsupervised color image segmentation ...

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... A **Gaussian** **Mixture** **Model** (GMM)[4] is a parametric probability density function represented as a weighted sum of **Gaussian** component ...parametric **model** of the probability distribution of ...

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... of **Gaussian** component ...parametric **model** of the probability distribution of continuous ...complete **Gaussian** **mixture** **model** is parameterized by the mean vectors, covariance matrices and ...

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... the **Gaussian** **Mixture** **Model** (GMC) is a standout amongst the most well-known component portrayals in speech acknowledgment [Davis and Mermelstein, ...

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... The commonly used approach for determining the parameters of a finite doubly truncated **Gaussian** **mixture** **model** from a given dataset is to use the maximum-likelihood estimation [1]. The EM algorithm is ...

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... The **mixture** of Gaussians background subtraction method is employed to detect both background and static foregrounds by using the same **Gaussian** **mixture** ...background **model** and the foreground ...

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