Speaker recognition is the most natural biometric identification technique. It can be divided into two sub-fields: speaker identification and speaker verification.
说话人识别是最自然的生物特征身份鉴定方式，可分为说话人辨认和说话人确认。
The baseline system we used is text-independent speaker identification system.
所采用的基线系统为文本无关的说话人辨认系统。
This paper presents a new method of real time lip contour extraction for multimodal speaker identification.
实现了一种用于说话人识别的实时唇线提取方法。
The experiment results indicate that the proposed method can significantly improve the speaker identification...
实验表明，这种方法能够有效的提高说话人识别系统的性能。
Vector Quantization(VQ)is one of the popular codebook design methods for text-independent speaker identification.
矢量量化（VQ）方法是文本无关说话人识别中广泛应用的建模方法之一，它的主要问题是码本设计问题。
This paper presented some conclusive results for Chinese speaker identification using GMM based on experimental analysis.
本文使用GMM方法，通过实验分析得出了基于GMM的汉语说话人识别的一些概括性结论。
The basic premise of speaker identification is that the interspeaker difference is bigger than the intraspeaker variation.
话者鉴别的一个基本前提是“个体间的语音差异大于个体的语音变异”。
Several new algorithms of fuzzy C-mean clustering with the combination of vector quantization are proposed for speaker identification.
该文提出了一种将模糊C -均值聚类法的各种改进算法与矢量量化法相结合的说话人辨认的新方法。
Experiment result shows the new mixed feature efficiently improves the speaker identification accuracy with better feature characterization.
实验结果显示，这种新的混合参数有效地提高了说话人的识别率，能更好地表征说话人的特征。
In a speaker identification system, training speaker models is computationally expensive, especially when the dimension of feature vectors is large.
在说话人识别系统中，通常训练说话人模型需要很长的时间，特别当说话人特征的维数很高时。
The goal of speaker identification systems is to extract, characterize and identify the information in the speech signal conveying speaker identity.
说话人辨认系统的目的是提取、特征化和辨认表征说话人身份的语音信号信息，因此它在身份验证领域具有广阔的应用前景。
The background noise leads a mismatch between the training environment and testing environment, and degrades the performance of speaker identification system.
背景噪声的存在，使得说话人识别系统的训练环境和测试环境发生失配，导致系统性能发生急剧下降。
Vector Quantization (VQ) is one of the popular codebook design methods for text-independent speaker identification. The key problem of VQ is the design of codebook.
矢量量化(VQ)方法是文本无关说话人识别中广泛应用的建模方法之一，它的主要问题是码本设计问题。
To solve the effect of channel changes on the performance of speaker identification system, apply the method of maximum a posteriori to specific channel compensation.
为了解决通道变化对说话人识别系统性能的影响，将最大后验概率方法应用到具体的通道补偿中。
This paper studies the speaker identification problem using support vector machine, and presents a SVM training method on large-scale training data according to the speech signal.
本文提出了用支持向量机来解决说话人辨认问题，结合语音信号的特点，解决了大数据量情况下支持向量机的训练问题。
For speaker identification, Expectation Maximization Algorithm (EM) is adopted to train speaker dependent model, and afterwards recognize speaker according to Maximum a Posteriori Criterion (MAP).
对于语者辨识，语者特定模型直接用语者的语料借助于期望值最大化算法（EM）来训练，辨识算法采用了最大事后概率法则（MAP）；
Speaker identification technology has appeared in industrial applications as a next generation security technology.
说话者识别技术作为一个新一代的门禁安防技术也已经出现商业应用。
Speaker identification technology has appeared in industrial applications as a next generation security technology.
说话者识别技术作为一个新一代的门禁安防技术也已经出现商业应用。
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