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tdpsolamatlab.rar
- 此程序在matlab环境下运行，是完整的tdpsola和fdpsola程序，包含了前期的语音读入，预处理，清浊音判决等等很全面,This procedure to run in matlab environment, is a complete program tdpsola and fdpsola include pre-read the speech, pre-processing, audio Qingzhuo comprehensive judgments, etc.
MFCCdeC
- 工程包括声音文件的读取、预处理、MFCC参数的提取、最后的聚类函数，对于做语音识别的人帮助很大-The works will include the sound files to read, pre-treatment, MFCC parameters extracted, the final clustering function, to do speech recognition for the great help of people
preprocess0
- 语音信号处理前的预处理部分，包括预加重，分frame，加窗，是语音信号编程入门的一个很好的参考程序-Speech signal processing part of the pre-pre-treatment, including pre-emphasis, sub-frame, plus window, the speech signal a good entry-programming reference procedures
voicematlab
- 语音信号预处理matlab程序，在7.0上运行通过，可以做实验参者代码。-Matlab voice signal pre-processing program, run through the 7.0, you can experiment with participation by the code.
fft
- 用于语音识别前端信号预处理的快速傅里叶变换，提高语音信号识别率！-Fast Fourier transform for speech recognition front-end signal pre-processing, improve the recognition rate of voice signal
vectorcprogram
- 自己用c语言写的关于语音识别中预处理过程中的矢量量化的程序，希望大家能用的上-C language used to write their own on the speech recognition pre-processing in the process of vector quantization procedure, the last hope that we can
duojishilianglbgvq
- 对于语音编码参数的有权重多级矢量量化，主要是对LSP码本训练，这个权重学习语音的都应知道，且这个可以训练大的语音参数，完全自已写的。上传前已调试成功。-Speech coding parameters for the right to re-multistage vector quantization, mainly for LSP codebook training, the right to re-learn voice should know, and that this can be t
VoiceActivityDetection
- 在本文中,主要讲了在语音识别和语音合成之前我们所要做的主要工作，包括去噪,预加重,端点检测,特征参数提取等技术.-In this article, the main speaker in the speech recognition and speech synthesis to be done before we have major work, including de-noising, pre-emphasis, endpoint detection, feature extraction
processspeech
- 语音识别系统，内涵许多处理函数，包括预处理、滤波和一些运算-Speech recognition system, meaning many processing functions, including pre-processing, filtering and a number of computing
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
Frame
- 语音识别中语音信号的的预加重与分帧程序。-Pre-emphasis and framing process in speaker recognition.
recognition
- 语音识别的端点检测工具,包括预处理，预加重，mfcc，端点检测。-Endpoint detection of speech recognition tools, including pretreatment, pre-emphasis, mfcc, endpoint detection.
mfcc_feature_extraction
- 本代码实现语音信号的特征提取功能，包含预加重，加窗，DFT变换，设置滤波器组，计算每隔滤波器输出，求取MFCC系数的全过程-The code feature extraction of speech signal features, including pre-emphasis, windowing, DFT transform, set the filter to calculate every filter output, to strike the entire process of MF
asdfasdfsad
- 在VC环境下实现对输入语音信号的预处理和各种算法变换，是一种实用的语音处理程序源码-In the VC environment to achieve the input speech signal pre-processing algorithms and all kinds of transformation, is a practical source of voice processing
Untitled10
- 基于自相关函数的基音检测算法，再此基础上进行中心削波预处理，估算出基音周期。-Autocorrelation function based pitch detection algorithm based on the center and then the pre-clipping, to estimate the pitch period.
blockframes
- 语音信号处理中用于说话认识别中预处理部分的分帧函数代码-Speech signal processing for speech understanding in other parts of the sub-frame in the pre-function code
speech-recognition
- 语音识别系统，包括预处理，汉明窗，梅尔频率倒谱率，离散余弦变换，前置滤波器组，对数能量，滤波器组，基本的滤波器组，dtw-speech recognition system，including Pretreatment, Hamming window, Mel frequency cepstrum rate, discrete cosine transform, pre-filter, log energy, filter, basic filter，dtw
pitchd
- 语音信号中基音检测。基于自相关方法的基因检测。包含预处理和后处理。-Pitch detection of speech signals. Autocorrelation method based on genetic testing. Includes pre-and post-processing.
Speech-enhancement-
- 基于matlab仿真的语音增强算法，语音增强是语音识别的预处理，通过语音增强可以很好的进行语言识别-Matlab simulation-based speech enhancement algorithms, speech recognition, speech enhancement is pre-processing, through the speech enhancement for speech recognition can be good
speech-recognition-pre-processing
- 本段程序包含了语音识别预处理中的采样、量化、预加重、分帧加窗等程序，另外添加了端点检测需要的短时能量、过零率的程序，经实验测试，运行结果符合理论期望-Procedures in this paragraph contains the voice recognition preprocessing sampling to quantify the pre-emphasis, framing windowed program, the addition of short-term energy ne