搜索资源列表
dzcpa
- 用在提高语音识别率的特征提取算法的程序,DZCPA是差分过领率和峰值检测的意思-spent on improving speech recognition rate of feature extraction algorithm procedures, DZCPA difference is the leading off and peak detection means
AudioSignalFeatureExtractionandClassificationUsing
- 语音特征提取中比较经典的文献,对学习语音特征的初学者来说非常有用.
1
- 摘要:一般的说话人识别系统包括特征提取和识别模型两部分,其中特征参数的选择对系统 的识别性能有关键性的影响,现就特征提取展开研究,介绍了各种常用的语音特征参数及目前 主流的两种参数的提取过程,并论述了小波分析应用于语音特征参数提取中的优势
hhh
- :由于许多传统的去噪方法在强背景噪声情况下提取声音信号的能力变弱甚至失效, 提出 应用独立成分分析( I C A) 方法对声音信号进行特征提取, 并证明了这种 I C A 变换能增强语音和音 乐信号的超高斯性. 在此基础上, 应用 I C A基函数作为滤波器, 通过阈值化的去噪方法对含有强高 斯背景噪声的声音信号进行去噪仿真实验. 结果表明, 本方法明显优于传统的均值滤波和小波去噪 方法, 为强背景噪声下弱信号的检测提供 了新的途径.-: As many of the t
MFCC-and-SVM
- 建立了普通话语音性别数据库,提出联合梅尔频率频谱系数(Mel2f requency Cep st rum Coefficient s , MFCC) 的特征提取方法和支持向量机(Support Vector Machine , SVM) 的分类方法进行说话人性别识别,并与其它分类方法进行比较。-A Chinese speech ( mandarin ) database was established for speaker s gender recognition. A combina
dtw
- 本为主要阐述了小波变换在语音信号去噪的应用,语音端点的检测,语音特征的提取及一种简单的语音识别算法。-This is mainly expounds the wavelet transform in the application of speech signal denoising, speech endpoint detection, speech characteristics of the extraction and a simple speech recognition algori
LPCC-VAD
- 用于语音特征提取算法matlab实现,以及重构语音信号-For voice feature extraction algorithm matlab realize, as well as reconstruction of the speech signal
PCA-KPCA
- 主成分分析(Principle Component Analysis, PCA)是最为常用的特征提取方法,被广泛应用到各领域,如图像处理、综合评价、语音识别、故障诊断等。-Principal component analysis (Principle Component Analysis, PCA) is the most commonly used feature extraction methods are widely applied to various fields, such as
ilplement-prefix-set
- 将原始语音经过预处理,利用频率弯折小波进行特征提取,不错的源码-The original speech after preprocessing, the use of frequency bending wavelet feature extraction, good source