搜索资源列表
Endpoint-detection
- 基于短时能量与过零率、倒谱特征和谱熵的三种语音端点检测-Endpoint detection
MATLAB
- 梅尔频率倒谱(Mel-Frequency Cepstrum)是一段声音的短时功率谱，基于频率的非线性梅尔刻度(mel scale)的对数能量频谱的线性预先变换- the mel-frequency cepstrum (MFC) is a representation of the short-term power spectrum of a sound, based on a linear cosine transform of a log power spectrum on a nonline
daopu
- 用matlab实现对于语音信号的倒谱计算，并绘制其倒谱图-Using matlab to calculate Cepstral voice signals, and draw their inverted spectrum
9MATLABCHULIXIN
- 第9章共振峰的估算方法259 9.1预加重和端点检测259 9.1.1预加重259 9.1.2端点检测260 9.2倒谱法对共振峰的估算260 9.2.1倒谱法共振峰估算的原理260 9.2.2倒谱法共振峰估算的MATLAB程序261 9.3LPC法对共振峰的估算262 9.3.1LPC法共振峰估算的原理262 9.3.2LPC内插法共振峰的估算263 9.3.3LPC求根法共振峰的估算266 9.4连续语音LPC法共振峰的检测268 9.4.1简
3MATLABYUYIN
- 3.1语音信号的同态处理和倒谱分析30 3.1.1同态处理的基本原理30 3.1.2复倒谱和倒谱31 3.2离散余弦变换34 3.3Mel频率倒谱系数的分析37 3.3.1Mel滤波器组37 3.3.2MFCC特征参数提取38 3.4小波和小波包变换43 3.4.1小波变换43 3.4.2小波包变换44 3.4.3小波包算法45 3.4.4MATLAB中一维小波和小波包变换函数46 3.4.5MATLAB语音信号小波和小波包变换的例子49 3.
speech-analysis
- 对语音进行分析，包括时域分析（包括能量、过零率、互相关函数）和频域分析（包括fft变换、倒谱、LPC）-Speech analysis, including time domain analysis (including energy, zero-crossing rate, the cross-correlation function) and frequency domain analysis (including fft transform, cepstrum, LPC)
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- 语音识别中的端点检测，是基于倒谱特征，可以检测出语音段-Speech Recognition endpoint detection is based Cepstral, can detect speech segments
Log-spectrum--spectrogram-cepstrum
- 对数谱 语谱图和倒谱代码 适用于语音识别 说话人识别 自己编写 亲测可以运行-Logarithmic spectrum and spectrogram cepstrum code for voice recognition speech recognition to write your own pro-test can be run
mfcc
- matlab版本，提取语音梅尔频谱倒谱系数（MFCC）特征-Matlab version, Mel frequency cepstrum coefficient（MFCC） feature extraction of speech
stft
- 里面包括短时傅里叶变换谱，倒谱平滑等，这些代码广泛用于，语音说话人识别，语音增强，雷达，声呐，图像等领域-Including short-time Fourier transform spectrum, cepstrum smooth, etc., are widely used in the code, voice speaker recognition, speech enhancement, radar, sonar, image, etc
quhunxiangDCT
- 运用复倒谱的方法,对信号进行去混响处理,将混响有效去除,被称为DCT法。-The method of using complex cepstrum of signal dereverberated will effectively remove the reverb, known as DCT method.
DAOPUFA1234
- 较为详细的介绍倒谱法，传统倒谱法以及对倒谱法的改进算法，以及对倒谱法进行MATLAB实验-A detailed introduction of cepstrum method, the traditional cepstrum method, and the cepstrum method of improved algorithm, and MATLAB experiments of cepstrum method
junhengqi
- 本程序是用MATLAB编写的孤立词的语音识别的程序，包含mel倒谱分析以及单个词的语音识别。-This procedure is used to prepare MATLAB isolated word speech recognition procedures, including mel cepstrum analysis, and single-word speech recognition.
voiceinotherdomain
- 语音信号在其他变换域中的分析技术和特性,语音信号的同态处理和倒谱分析,离散余弦变换,小波和小波包变换-Speech signal analysis technologies and features in other transform domain, homomorphic processing voice signals and cepstrum analysis, discrete cosine transform, wavelet and wavelet packet transform
lpcc
- 这是应用MATLAB求解线性预测倒谱的程序代码，验证有效-this is the application of MATLAB to solve linear predictive cepstrum code, validated
daopujuli
- 基于倒谱距离的语音信号端点检测方法的matlab程序，可以用于语音信号端点检测-Cepstral distance voice signal endpoint detection method based on the matlab program that can be used for voice signal endpoint detection
logSpectrumthe-spectrogram--cepstrum
- 语音对数谱，语谱图，倒谱的代码，自己编写的，可以运行-Speech log spectrum, the spectrogram, cepstrum of the code, I have written, you can run
daopu
- 浊音倒谱图的matlab实现，包括语音信号的分帧、加窗，取一帧进行分析。-Dullness inverted spectrum realize the matlab，ncluding sub-frame of the speech signal, windowing, take a frame for analysis
m_files
- MFCC，Mel频率倒谱系数的缩写。Mel频率是基于人耳听觉特性提出来的，它与Hz频率成非线性对应关系。Mel频率倒谱系数(MFCC)则是利用它们之间的这种关系，计算得到的Hz频谱特征，MFCC已经广泛地应用在语音识别领域。-MFCC, Mel Frequency Cepstral Coefficients abbreviations. Mel frequency is proposed based on the human auditory characteristics. It comes
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- 对原始语音帧进行处理，然后进行预测，最后显示出倒谱之类的东西-The original speech frame processing, and then forecast, and finally show that the class of the like