搜索资源列表
spkID
- 利用mFCC特征提取算法进行语音信号的特征提取，然后利用ＧＭＭ识别出特征人，计算目标得分，程序效果ＯＫ。(The extraction algorithm for feature extraction of speech signal using mFCC features, and then use GMM to identify a specific target, calculate the score, the effect o
kmm_mfcc
- 利用MFCC進行特徵截取，在利用KNN進行比對(Feature interception with MFCC and alignment with KNN)
vad
- mfcc-matlab, speech signal using matlab realize the MFCC feature recognition method
matlab语音识别系统(源代码)
- 基于mfcc参数的语音识别，matlab代码，可以对孤立语音词识别(Speech recognition based on MFCC parameters, matlab code, can identify isolated speech words)
rebuilt.HumanTimbre_recognition-master
- 利用mfcc特性进行语音识别，分类算法为svm。(Speech recognition using MFCC characteristics)
HMM with skips and single Diagonal Gaussian
- 以MFCC作为特征参数，利用HMM算法进行语音识别(Speech recognition using HMM algorithm)
SpeechRecognitionHMM-master
- java实现语音信号的识别，利用MFCC等参数和HMM模型(Java realizes the recognition of speech signals, and utilizes MFCC and other parameters and HMM models.)
语音情感识别程序
- 利用matlab来识别语音情感特征，使用mfcc和dtw(Recognition of emotional characteristics of speech)
基于Labview的语音识别程序
- 语音识别代码，基于labview，有labview程序，希望有所帮助(dggfeefadsffsfsagfagdgdsg)
171724210736171
- 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。(Speech signal feature extraction)
project2
- 基于mfcc和DTW的孤立字词识别源码，可实现简单的语音识别(Based on isolated word recognition and source mfcc DTW can achieve a simple voice recognition)
mfcc_svm
- mfcc特征提取法 以及svm训练 可以使用(MFCC feature extraction method and SVM training can be used)
hmm声音识别
- CHMM语音识别程序，十个字的识别。隐式马尔科夫模型。(CHMM Speech Recognition Program, Recognition of Ten Characters)
mfcc
- 语音端点检测,利用梅尔频率和谱熵进行的语音端点检测(voice activity detection)
SpeakerVoiceIdentifier-master
- 用C++完成的基于MFCC和GMM的说话人识别软件。(Speaker recognition software based on MFCC and GMM is completed with C++.)
voicerecognition
- 用matlab进行的说话人识别，计算方法是mfcc，识别精度很高(This is a speaker recognition, using mfcc)
情感
- 基于svm的情感识别系统，有gui界面，特征提取是用mfcc。(The emotion recognition system based on SVM has GUI interface and MFCC is used for feature extraction.)
GMM模型建立和mfcc参数的取得方法
- 高斯模型就是用高斯概率密度函数（正态分布曲线）精确地量化事物，将一个事物分解为若干的基于高斯概率密度函数（正态分布曲线）形成的模型。