Description: 说话人识别和训练系统所用的很多源码，内容很详实，希望大家能用的上-Speaker Recognition and training system used by a lot of source code, content is very informative and hope that we can use the upper Platform: |
Size: 8192 |
Author:姜海鹏 |
Hits:
Description: Wavelet Subband coding for speaker recognition
The fn will calculated subband energes as given in the att tech paper of ruhi sarikaya and others. the fn also calculates the DCT part. using this fn and other algo for pattern classification(VQ,GMM) speaker identification could be achived. the progress in extraction is also indicated by progress bar.-Wavelet Subband coding for speaker recognitionThe fn will calculated subband energes as given in the att tech paper of ruhi sarikaya and others. The fn also calculates the DCT part. Using this fn and other algo for pattern classification (VQ, GMM) speaker identification could be achived. the progress in extraction is also indicated by progress bar. Platform: |
Size: 88064 |
Author:chan man man |
Hits:
Description: 高斯混合模型[Gaussian mixture model,简称GMM]是单一高斯机率密度函数的延伸,由於GMM 能够平滑地近似任意形状的密度分布,因此近年来常被用在语音与语者辨识,得到不错的效果。 -Gaussian mixture model [Gaussian mixture model, referred to as GMM] are single-Gaussian probability density function of the extension.GMM can approximate arbitrary smooth shape of the density distribution, so it is often used in speech and speaker recognition in recent years. Platform: |
Size: 63488 |
Author:杨清山 |
Hits:
Description: 使用GMM模式建立的语音识别系统，matlab源代码，供大家参考！-GMM model using the speech recognition system, matlab source code for your reference! Platform: |
Size: 1024 |
Author:王良 |
Hits:
Description: 高斯混合模型是單一高斯機率密度函數的延伸，由於GMM 能夠平滑地近似任意形狀的密度分佈，因此近年來常被用在語音與語者辨識，得到不錯的效果。-Gaussian mixture model is a single Gaussian probability density function of the extension, as the GMM can approximate arbitrary smooth shape of the density distribution, it is often used in recent years in speech and speaker recognition, get good results. Platform: |
Size: 195584 |
Author:geyu |
Hits:
Description: Speaker Recognition by training GMM models for the speakers in the system. Also tells if there s an impostor in the system. Platform: |
Size: 560128 |
Author:sam |
Hits:
Description: 在实时平台上,高斯混合模型(GMM)具有计算有效性和易于实现的优点。最大似然规则中,模型参数不
断更新,但由于爬山特征,任意的原始模型参数估计通常将导致局部最优 遗传算法(GA)适于求解复杂组合优化问
题及非线性函数优化。提出了基于说话人识别的可以解决GMM局部最优问题的GMM/GA新算法,实验结果表明,
提出的GMM/GA新算法比纯粹的GMM算法能获得更优的效果。
- In real-time platform, the Gaussian mixture model (GMM) with the calculation of the effectiveness and easy to realize benefits. Maximum likelihood rule, the model parameters are not
Broken updates, but due to climbing features, any of the original model parameter estimation will usually result in local optimum genetic algorithm (GA) is suitable for solving complex combinatorial optimization question
Title and non-linear function optimization. Proposed speaker recognition based on GMM can solve the problem of local optimal GMM/GA new algorithm, experimental results show that the
Proposed GMM/GA new algorithm than purely GMM algorithm can get better results. Platform: |
Size: 4448256 |
Author:于高 |
Hits:
Description: 这个是用Matlab写成的说话人识别演示程序。-Currently, there are more than 20 classes in this library, including commonly used feature extraction algorithms and modeling techniques for speech recognition and speaker verification.-Currently, there are more than 20 classes in this library. including commonly used feature extraction al gorithms and modeling techniques for re speech cognition and speaker verification. Platform: |
Size: 2451456 |
Author:liximin |
Hits:
Description: automatic Speaker recognition system using Gmm and Mf-automatic Speaker recognition system using Gmm and Mfcc Platform: |
Size: 576512 |
Author:vikram |
Hits:
Description: 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 (vector quantization) and GMM (Gaussian mixture model) approaches. For the research and experiments we created and exploited database, containing specially prepared short speech sequences. Platform: |
Size: 258048 |
Author:Tomasz |
Hits:
Description: 使用voicebox进行说话人识别,初步介绍如何用GMM（Gaussian Mixture Model）的方法来进行说话人辨识（Speaker Identification），并在Matlab下，尝试通过调整参数来提高得分-For speaker recognition using the voicebox, initially describes how to use GMM (Gaussian Mixture Model) approach to speaker recognition (Speaker Identification), and in Matlab, try to increase the score by adjusting the parameters Platform: |
Size: 9216 |
Author:戴平平 |
Hits:
Description: 基于MATLAB环境下的GMM建模的程序代码,可用于说话人识别系统-Can be used for speaker recognition system based on the the GMM modeling program code in the MATLAB environment, Platform: |
Size: 243712 |
Author:温俊荣 |
Hits:
Description: 基于GMM的说话人识别，搭建了一个说话人识别系统用于试验测试，验证了一些参数对性能
的影响，同时使用了多线程并行处理技术，以此缩短识别时间:并提出了一种放
大特征向量差距，变换特征向量在特征空间的分布来提升大容量语音库中说话人
识别率的方法。
-GMM-based speaker recognition, to build a speaker recognition system used for pilot testing to verify the performance impact of some of the parameters, using a multi-threaded parallel processing technology, in order to shorten the recognition time: and presents a zoom feature Vector gap, transformed feature vector in the feature space to improve the distribution of large speech database speaker recognition rate method. Platform: |
Size: 3444736 |
Author:李倩倩 |
Hits:
Description: 介绍UBM模型MAP算法过程，对于说话人识别有帮助-UBM model describes the process of MAP algorithm for speaker recognition helpful Platform: |
Size: 166912 |
Author:李丽 |
Hits:
Description: 微软研究院的说话人识别工具包，包括GMM-UBM、I-Vector。其中demo_gmm_ubm_artificial.m和demo_ivector_plda_artificial.m为生成模拟特征参数进行训练与识别的教学示例，十分适合初学者学习说话人识别基础算法。具体使用方法请看内部文档。-Microsoft Research s speaker recognition toolkit, including GMM-UBM, I-Vector. Demo_gmm_ubm_artificial.m and demo_ivector_plda_artificial.m which generates an analog characteristic parameters for example teaching training and recognition, very suitable for beginners to learn the basic algorithm for speaker recognition. See the specific use of internal documents. Platform: |
Size: 2437120 |
Author:尹海明 |
Hits:
Description: The short synopsis consists of the explanation for speaker recognition using gmm and mf-The short synopsis consists of the explanation for speaker recognition using gmm and mfcc Platform: |
Size: 1620992 |
Author:saurabh |
Hits:
Description: The number of states in GMM as the generative model of the frames is obtained using
k-means algorithm. This also helps to initialize the mean vector and the covariance
matrix of the individual state of the GMM. The training LPC frames collected from
three speech segments are subjected to PCA for dimensionality reduction and are
subjected to k-means algorithm. The total number of frames is equal to the total
number of vectors that are subjected to k-means clustering. Platform: |
Size: 728064 |
Author:Khan17
|
Hits:
Search - gmm for speaker recognition