搜索资源列表
SPlatForm
- 我自己用vc写的语音特征提取程序，执行程序后，在上面的搜索前输入你的音频文件的路径，按搜索就回把把结果存放到e:/tt.dat里面，你还要在e盘建立一个tt.txt文件-I write with vc voice feature extraction procedures, implementation procedures, in the above search before you import the audio files path, according to search put b
Feature-0.95
- 语音特征库，比较充分，可以结合语音识别平台一起使用-voice feature library is full, can combine voice recognition platform used together
speech_analysis
- 这时一个语音特征提取的程序源码，除了包含矩阵运算和矢量运算外，还包含了很多语音特征的提取算法，包括：共振峰(formant)提取、基音(pitch)提取、端点(endpoint)检测、线性预测系数(LPCC)、MFCC、LSF、PLCC、EPOCH等。这是我见到的最全的语音分析源码，推荐！-Then a voice feature extraction procedures source, in addition to containing matrix and vector operation
lpcdaopu
- 可以求出语音信号的LPC倒谱特征向量，该特征向量在语音信号分析中得到了广泛的应用。-voice signal can be obtained by LPCCEP eigenvector, the eigenvector of the voice signal analysis has been widely used.
matlabyuyinshibiesuanfa
- matlab语音识别算法，包括预处理，特征提取，训练，识别算法，基于hmm模型-Matlab speech recognition algorithms, including preprocessing, feature extraction, training, recognition algorithm based on model hmm
praat5107_sources.语音识别中语音特征参数提取的工具
- 语音识别中语音特征参数提取的工具，对于语音参数分析有很好的作用,Speech recognition speech feature extraction tools for speech parameter analysis, have very good effect
SpeechSignalFeatureExtractioncprogram
- 主要描述了基于特定人语音信号特征提取以及相关代码-Mainly describes the people on the basis of specific speech signal feature extraction and related code
LD
- 语音识别中lpc特征提取算法，采用LEVINSON-DURBIN算法，c编程，简单易懂，还包含该算法原理的word详细说明资料。-Lpc speech recognition feature extraction algorithm using LEVINSON-DURBIN algorithm, c programming, easy-to-read, the algorithm also includes detailed information of the word.
MATLAB-YUYINSHIBIE
- 这是语音识别的几个程序，包括语音的特征提取、端点检测的程序。-This is the number of speech recognition procedures, including the voice feature extraction, endpoint detection procedure.
speechcode1
- matlab中用于输入语音信号，特征提取，建立模型，识别判决等三部分的源码。-matlab input speech signal is used, feature extraction, modeling, identification judgments, such as the source of three parts.
fenzhenchuli
- 语音特征提取，如过零率，能量比，短时能量。须导入MAV音频。-Voice feature extraction, such as zero-crossing rate, energy ratio, short-term energy. MAV audio to be imported.
DTWspeech
- 本 文 首先 介绍了语音识别的研究和发展状况，然后循着语音识别系统的 处理过程，介绍了语音识别的各个步骤，并对每个步骤可用的几种方法在实 验基础上进行了分析对比。研究了语音信号的预处理和特征参数提取，包括 语音信号的数字化、分帧加窗、预加重滤波、端点检测及时域特征向量和变 换域特征向量.其中端点检测采用双门限法.通过实验比对特征参数的选取， 采用12阶线性预测倒谱系数作为识别参数。详细分析了特定人孤立词识别算 法，选定动态时间弯折为识别算法，并重点介绍其设计实现。 在
mfcc
- 语音信号的初始化及MFCC特征提取算法，附带测试用语音信号-Voice signal and the initialization MFCC feature extraction algorithm, with test speech signal
MATLAByysb
- 用MATLAB进行语音识别的特征参数提取，其中包含了lpc和MFCC两种方法，并且测试通过。-Using MATLAB to carry out speech recognition feature extraction, which contains two methods lpc and MFCC, and the test.
MFCC
- 为了实现高速语音特征参数的提取，在分析了美尔频率倒谱特征参数提取算法的基础上，提出了算法的硬件 设计方案，介绍了各模块的设计原理。该方案增加了语音激活检测功能，可对语音信号中的噪音帧进行检测，提高了特征参 数的可靠性。-In order to achieve high-speed voice characteristic parameter extraction, in the analysis of Mel frequency cepstral feature extraction a
spectrum
- 对功率谱的估计，可对图像，语音等多媒体文件进行功率谱计算后进行特征提取-Of the power spectrum estimate, the image, voice and other multimedia files after calculating the power spectrum feature extraction
案例1 BP神经网络的数据分类-语音特征信号分类
- 使用BP神经网络的数据分类-语音特征信号分类(Data classification using BP neural networks -- speech feature signal classification)
audio-feature-extraction
- 音频的特征提取，是用python写的，里面有readme可以查看(audio features extraction)
LPCC
- 线性预测倒谱系数（Linear Prediction Cepstrum Coefficient,LPCC）是线性预测系数（Linear Prediction Coefficient,LPC）在倒谱域中的表示。该特征是基于语音信号为自回归信号的值设，利用线性预测分析获得倒谱系数。(Linear Prediction Cepstrum Coefficient)
yuchuli1
- 基于python平台的语音信号的预处理和MFCC39维度的特征提取(MFCC based on python)