speaker recognition的例句大全

This paper focuses on the speaker recognition system based on Mel-Frequency Cepstrum Coefficients ( MFCC) and Gaussian Mixture Model ( GMM).

在众多的说话人识别技术中，本文主要研究了基于Mel频率倒谱系数（Mel-Frequency Cepstrum Coefficients，简称MFCC）和高斯混合模型（Gaussian mixture model，简称为GMM）的说话人识别系统。

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Automatic speaker recognition is the processing of automatically recognizing who is speaking by using speaker specific information included in speech signal.

自动说话人识别是指根据包含在语音中的同说话人有关的信息来自动识别说话人。

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The speech signal is essentially continuous, so the speaker recognition rate can be improved if we obtain the temporal correlation in the frames.

语音信号本质上具有连续性，所以获取语音帧特征之间的时变特性，将对识别的性能带来提高。

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Up to now, the technology using in speaker recognition is most based on conventional linear system theory, but the speaker recognition itself is a complex nonlinear assoeted process.

目前，应用于说话人识别的技术大都是基于传统线性系统理论，但说话人识别本身是一个复杂的非线性分类过程。

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Study of Speaker Recognition System Based on VQ

基于VQ的声纹识别研究

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A separability research of prosodic parameters in speaker recognition is studied.

对音高特征在说话人识别中的可分性问题进行了分析和实验研究。

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Speaker recognition is the process of automatically recognizing who is speaking on the basis of individual information include in speech signals. It has well application prospects in many fields.

说话人识别是指通过说话人的语音来自动识别说话人的身份，它在许多领域内有良好的应用前景。

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Study on Speaker Recognition under Noise Environment Based on Probability DP Matching Algorithm

基于概率DP匹配法的噪声环境下说话人识别方法的研究

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The improved speaker recognition system based on model distance measure

一种基于模型距离的改进的说话人识别技术

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Study on Speech Feature Extraction Algorithm in Speaker Recognition System

说话人识别中语音特征参数提取方法的研究

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Speech Filtered Recognition, a novel Automatic Speaker Recognition, and discuss its goodness and badness.

言语过滤识别方法：一种新型的说话人识别方法。

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Now we uses cluster validity analysis for refrence and improve it. The new codebook training algorithm can choose the size of codebook automatically and improve the performance of speaker recognition.

本文借助聚类有效性分析，对常用的电码本训练算法进行了改进，其主要目的就是实现电码本大小的自动设定并提高说话人识别性能。

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In this situation, speaker recognition system could suffer great performance attenuation.

常用的说话人识别系统在这种变化的环境下，识别性能会遭受较大的衰减。

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In the process of speech and speaker recognition with BP neural network, nearly several hundreds of input nodes are required, that lead a very large network scale and a very slow train speed.

在用BP网进行语音和说话人识别过程中，BP网的输入节点数一般在几百个左右，使得网络的规模过大，训练速度过慢。

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Study and Simulation of the Acoustic Features in Speaker Recognition System

话者识别系统中语音特征参数的研究与仿真

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svm can only classify two classes, how to solve speaker recognition, a problem of classifying multi-class, is the key of our task.

如何将解决二元分类的SVM用于说话人识别这一多元分类问题中，是本课题的关键。

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Design of speaker recognition system based on parallel genetic algorithm

基于并行遗传算法的说话人识别系统设计

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The second issue is the use of discrimination transform of LDA in speaker recognition.

本文的第二个工作是研究了线性判别分析（LDA）的区分性变换在说话人识别中的应用。

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This paper realized a speaker recognition system based on Gaussian Mixture Models ( GMM).

实现了一个基于高斯混合模型（GMM）的说话人辨识系统。

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In algorithm ways, Gaussian mixture model ( GMM) is the most successful speaker recognition model at present.

在算法方面，高斯混合模型（GMM）是目前最成功的一种说话人识别模型。

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