搜索资源列表
cdhmm
- matlab下实现的用于语音识别的一些算法，包括hmm参数提取，viterbi识别算法，mfcc参数提取算法，端点检测算法等，对于做语音识别的来说都是很有用的-under Matlab for the voice recognition algorithm, including hmm parameter extraction, Recognition Viterbi algorithm, mfcc parameter extraction algorithm, endpoint detecti
mfcc
- 语音识别用到的特征提取，c程序编写的，可以运行，输入音频文件，可以得到特征向量。-Used by the speech recognition feature extraction, you can run the c programming, input audio file, you can get the feature vector.
mfcc
- 本程序是语音识别领域的重要组层部分，提供了提取语音信号Mel倒谱系数的解决方法。-This program is an important field of speech recognition group layer portion, providing a voice signal extraction Mel cepstral solution.
mfcc
- MFCC已经广泛地应用在语音识别领域。由于Mel频率与Hz频率之间非线性的对应关系，使得MFCC随着频率的提高，其计算精度随之下降。因此，在应用中常常只使用低频MFCC，而丢弃中高频MFCC。这个程序是求MFCC 的-MFCC has been widely used in speech recognition. Mel frequency Hz as a nonlinear correspondence relationship between the frequency, such as t
mfcc
- 语音识别中的lpcc算法，可以运行得出结果-Speech Recognition lpcc algorithm, you can run the outcome
mfcc
- 应用于语音识别，基于matlab,结合倒谱系数的动态和静态来实现语音识别-Used in speech recognition, based on matlab, combining cepstral coefficients to achieve static and dynamic speech recognition
mfcc
- mfcc.m 用于语音识别上的mfcc特征参数提取函数。-mfcc.m mfcc characteristic parameters for speech recognition on the extraction function.
MFCC
- MFCC参数提取的所有程序，已接近人耳听觉的特点在语音识别领域得到广泛应用-MFCC parameter getting
MFCC
- 用于语音识别中的MFCC特征系数的提取，并包含mel滤波子函数-Used to extract the speech recognition feature MFCC coefficients and contains mel filter Functions
mfcc
- 语音信号处理中MFCC特征提取程序，用于语音识别的特征提取-Speech Signal Processing MFCC feature extraction program for speech recognition feature extraction
mfcc
- 语音识别MFCC特征提取matlab代码。 「梅尔倒频谱系数」（Mel-scale Frequency Cepstral Coefficients，简称MFCC），是最常用到的语音特征，此参数考虑到人耳对不同频率的感受程度，因此特别适合用在语音辨识。-Speech recognition MFCC feature extraction matlab code. \ Mel cepstrum coefficient (Mel- scale Frequency Cepstral Coefficien
MFCC
- 语音识别中的MFCC算法，用MATLAB实现。-MFCC algorithm with MATLAB.
MFCC
- 用C++写的语音识别中的MFCC特征提取 有详细代码注释-feature extraction of MFCC BY C++
Voice Discern For STM32F
- 于市售 STM32 开发板上实现特定人语音识别处理项目。识别流程是：预滤波、ADC、分帧、端点检测、预加重、加窗、特征提取、特征匹配。端点检测(VAD)采用短时幅度和短时过零率相结合。检测出有效语音后，根据人耳听觉感知特性,计算每帧语音的 Mel 频率倒谱系数(MFCC)。然后采用动态时间弯折(DTW)算法与特征模板相匹配,最终输出识别结果。先用Matlab对上述算法进行仿真，经数次试验求得算法内所需各系数的最优值。而后将算法移植到 STM32 开发板上，移植过程中根据 STM32 上存储空间相
mfcc
- 改程序的功能：在进行语音识别时，完成对采集到的信号进行MFCC参数提取-The app features: when making the speech recognition, to complete the collected signal MFCC parameters extraction
mfcc
- 本文根据孤立词语音识别系统的处理步骤，从语音信号的预处理开始，分别详细说明了每个过程，比如预加重、分帧加窗和端点检测。接着介绍了特征参数MFCC的原理与选取，最后介绍了DTW算法的特点-In this paper, based on the process steps of isolated words speech recognition technology, starting with the speech signal pre-processing, each process is
DigitRecognization
- 矢量量化梅尔倒谱系数孤立词识别，识别说话者声音(speech recognition VQ MFCC)
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)
SpeechRec.part
- MATLAB下，采用DTW算法进行语音识别，其中特征参数的提取（MFCC）(MATLAB, DTW algorithm is used to recognize speech, and the extraction of feature parameters (MFCC).)
MFCCs
- 将语音识别领域的MFCC方法通过修改能够对三维地震数据进行特征提取实现了语音识别方法在地震信号方面的运用(The MFCC method in the field of speech recognition can be modified to extract the features of 3D seismic data to realize the application of speech recognition method in seismic signal)