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The BYY annealing learning algorithm for Gaussian mixture with automated model selection
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Gaussian mixture model
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:高斯混合模型(GMM)是一种经典的说话人识别算法，本文在实现其算法的同时，主要模拟了不同噪声环境情况下高斯混合模型
(GMM)的杭嗓声性能，得到了一些有益结论。
-Gaussian mixture model (GMM) is a classic speaker recognition algorithms, this algorithm at the same time in fulfilling its main simulated environmental conditions
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Implementation of background subtraction algorithm using Gaussian mixture model.
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Gaussian Mixture Model
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it is a Gaussian Mixture Model(MATLAB version) for training and testing with some list or file.
and it has references in enclosed rar file
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GMM高斯混合模型大规模概率对数计算
需要一个模型地址文件和一个需要识别的声音的mfc文件可以一次执行大批量-GMM Gaussian mixture model probability on the number of large-scale computing need a model of address file, and the voice of the mfc file which need to be identified .can be an implementation
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高斯混合模型参数初始化程序，在对高斯混合模型的建立之前采用KMEANS算法进行初始化-Gaussian mixture model parameter initialization procedure, in the Gaussian mixture model is initialized before the algorithm used KMEANS
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This paper presents results of speaker recognition experiments using short Polish sentences. We developed and analyzed various vector quantization representations in order to first maximize identification effectiveness and second to compare VQ (vecto
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基于高斯混合模型的说话人确认系统基于高斯混合模型的说话人确认系统-Recognized in the Gaussian mixture model-based speaker system
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基于高斯混合模型的说话人识别，可以直接运行-Based on gaussian mixture model the speaker recognition
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Gaussian Mixture Model is a Model which is used to simulate the data set into a statistical model.
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Finally, probability analysis, based on the chosen database, is performed and
judgment whether the person is recognized is pronounced. Two different modeling
techniques can be suggested for purposes of person identification or verification. The
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传统的短时谱估计语音增强算法通常假设语音谱分量相互独立，没有考虑语音谱分量间的相关性。针对这
一问题，该文提出一种新的基于多元Laplace分布模型的短时谱估计算法。首先，假设语音的离散余弦变换(DCT)
系数服从多元Laplace分布，以此利用谱分量间的相关性；在此基础上，利用多元随机矢量的高斯尺度混合模型表
示，推导得到语音DCT系数矢量的最小均方误差(MMSE)估计的解析表达式；并进一步推导了基于该分布模型的
语音存在概率，对最小均方误差估计子进行修正。实验结果表明，该算法
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语音处理GMM相关算法,1.计算概率密度并画出高斯混合模型，2.计算边际，条件混合高斯密度,3估计两个GMM模型的Kullback-Leibler divergence。-GMM relating to speech processing algorithms.1,to calculate probability densities from or plot a Gaussian mixture model.2,marginal and conditional Gaussian mixture
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Gaussian Mixture model
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Julius 是一种高性能，两通大词汇量连续语音识别（LVCSR）语音相关的研究和开发的解码器软件。基于字的N-gram和上下文相关的HMM模型，它可以进行几乎实时实时解码目前大多数电脑在60K字听写任务。完全纳入，如树的N-gram词汇，保，跨词的上下文依赖处理，包围梁搜索，高斯修剪，高斯的选择，除了搜索效率等各大搜索技术，它也是模块化小心从模型结构独立，如共享状态triphones的和并列混合模型与任意数量的混合物，州或手机，支持各种HMM的类型。采用标准格式，以配合HTK的，债务工具中央结
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本文介绍了基于MATLAB的语音识别系统，包括对语音信号的特征提取，包括语音信号的特征提取，快速傅立叶变换，离散余弦转换，线性预测分析，梅尔频率倒谱系数以及高斯混合模型。-This paper aims at development and performance analysis of a speaker dependent speech recognition
system using MATLAB® . The issues that were considered are 1
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