搜索资源列表
SpeakerRecognitionsystem
- 本程序是用MATLAB设计并实现一个简单的说话人识别系统,其主要功能模块包括语音信号的输入管理模块 ,语音的鉴别即特征提取块,语音的认证模块,程序很全. -this procedure is used MATLAB design and implement a simple speech recognition system, Its main function modules including voice signal input management module, voi
MusicSegmentation_F02
- 音频流提取 音频特征提取 音频分类 可用于说话人模型训练,静音,音乐和背景音的分类-Audio Streaming Audio extraction feature extraction can be used for classification of Audio speaker model training, quiet, Music and background noise classification
mplayer_classical
- Media Player Classical-Audio player是一个基于Mplayer2控件的音频播放器（视频也可以播放，但是...），所有Mplayer2支持的文件格式本程序都支持。本程序的一大特色是漂亮的播放列表（位于左下角）。所有的列表都保存在“曲目列表”文件夹中，你若愿意可以手动编辑。-Media Player Classical-Audio player is a Mplayer2 controls on the audio player (also can play vide
sndpeek
- sndpeek is just what it sounds (and looks) like: real-time 3D animated display/playback can use mic-input or wav/aiff/snd/raw/mat file (with playback) time-domain waveform FFT magnitude spectrum 3D waterfall plot lissajous! (inte
LEDCLOCK
- Applet Name: Sentence Applet Source: Sentence.java Import(s): java.applet, java.awt, java.io, java.lang, java.util Feature(s): text, image, animation, mouse-Applet Name: Sentence Applet Source: Sentence.java Import (s): java.applet, java.awt
GoldWave
- 比较好用又小的声音处理器，含转换功能。对多媒体初学者来说既简单又好用。-Comparison of the voice of small-to-use processors, including the conversion feature. For multimedia beginners is simple and easy to use.
freetalk
- 实现了简单的语音聊天功能，其中涉及到一些API函数，比如waveIn,waveOut等-Implements a simple voice chat feature, which involves some API functions, such as waveIn, waveOut, etc.
mic_file
- 一个基于麦克风的小控件，可以嵌入网页也可以直接在VB里调用。功能是开启录音，并将语音数据存成文件放在硬盘里。-A small microphone-based controls can be embedded in web pages can also be invoked directly in VB. Feature is on recording, and voice data stored as files on the hard disk.
mplayerdll-src
- The article ‘Use mplayer as our audio decoder’ introduces how to set compile environment and how to build mplayer as a single DLL library, and use it as a decoder to decode more audio format and playback. This article will go to the next step –
SVM
- MATLAB結合HTK的特徵擷取應用SVM函式 的實際範例 並且可達到即時錄音辨識 輸出 前三個語音辨識的機率 -MATLAB with HTK feature extraction practical examples of application of SVM function and can reach the probability of the first three speech recognition in the real-time recording identificat
harmonic
- 语音harmonic特征提取，先对语音信号分帧，然后对每一帧使用中心频率维基音频率的倍数的带通滤波器进行滤波，最后滤波结果的傅立叶变换的结果-Voice harmonic feature extraction, the first speech signal sub-frame, and then using the center frequency for each frame of Wiki sound frequency multiple of the band-pass filter f
Audio-feature-extraction
- 这是一个音频特征提取的matlab源代码-This is an audio feature extraction matlab source code
read_wav
- 提供功能查看不同类型的wav文件的文件头，并根据文件头的信息读取wav文件的数据信息，并可选择将数据输出到控制台或者文本文件中。-Feature to see different types of wav file header and data read wav file header information, and can choose to output the data to the console or text file.
MFCCEX
- MFCC 特征提取。用于语音识别等方面，通过特征提取，然后再进行识别操作-MFCC feature ,using voice recognition
ydwmfcc
- This a source code for acoustic feature extraction. The mel-cepstral feature is extracted from the audio signal used for speech recognition.-This is a source code for acoustic feature extraction. The mel-cepstral feature is extracted from the audio s
mfcc
- feature extraction for speech recognition
progress-6
- this audio retrieval based on the feature extraction such as FFT, STFT, and Power Spectral Density-this is audio retrieval based on the feature extraction such as FFT, STFT, and Power Spectral Density
B.Lucas
- 这是KLT算法论文的高清版。Kanade-Lucas-Tomasi方法，在跟踪方面表现的也不错，尤其在实时计算速度上，用它来得到的，是很多点的轨迹“trajectory”，并且还有一些发生了漂移的点，所以，得到跟踪点之后要进行一些后期的处理，说到Kanade-Lucas-Tomasi方法，首先要追溯到Kanade-Lucas两人在上世纪80年代发表的paper：An Iterative Image Registration Technique with an Application to Ste
A_subspace_algorithm
- 子空间算法是一种基于矩阵特征空间分解的方法，信号子空间由阵列接收到的数据协方差矩阵中与信号对应的特征向量组成噪声子空间则由协方差矩阵中所有最小特征值噪声方差对应的特征向量组成。子空间算法就是利用这两个互补空间之间的正交特性来估计空间信号的方位-Subspace algorithms is minimized by the corresponding eigenvalues of all the noise variance-covariance matrix of a
mfcc2delta
- In this work, the Mel frequency Cepstrum Coefficient (MFCC) feature has been used for designing a text dependent speaker identification system. The extracted speech features (MFCC’s) of a speaker are quantized to a number of centroids using v