speech_vad

4基于稀疏编码的语音增强方法.pdf (4 sparse coding speech enhancement based on 4 sparse coding speech enhancement method based on.Pdf.Pdf method)

通常语音信号在增强时会出现混响现象，演讲者为了消除背景混响，不得不频繁地偏转头部的方向，这样会造成脉冲响应的不断改变。我们结合盲解卷法和频谱消去法来提高逆滤波器的滤波效果。我们利用输入语音信号间的相关系数矩阵计算出稳定、精确的室内脉冲响应的逆滤波器，而这些输入信号无需测量室内的脉冲响应就能被观测到。逆滤波能够消除早期的反射，这些反射包含混响中的绝大部分能量。之后，用频谱消去法来抑制逆滤波后的信号的尾部混响。本方法在实际适应性方面的表现通过具体的实验进行了验证，结果表明盲解卷法和频谱消去法的结合相较于单独使用一种方法，能够提供一个更优越的演说环境。(Usually voice signal will be enhanced when the reverberation phenomenon, the speaker in order to eliminate the background reverberation, and had to frequently deflect the direction of the head, this will cause the impulse response of changing. We combine the blind deconvolution and spectral elimination method to improve the filtering effect of the inverse filter. We use the correlation coefficient matrix between the input speech signal to calculate the stable, accurate inverse filter of the indoor impulse response, and these input signals do not need to measure the room impulse response can be observed. Inverse filtering to eliminate early reflections, these reflections contains most of the energy in the reverberation. After the spectrum elimination method to suppress the tail reverberation of the signal after the inverse filtering. Performance in the actual adaptation of the method by specific experimental validation results show that the blind deconvolution and spectrum to eliminate )

EVRC的语音编码算法研究及仿真,及二阶固定码本搜索算法(Speech Coding Algorithm and Simulation of EVRC)

speaker recognition using MFCC GMM EM

评书,语音小说下载程序,修改一下可批量下载(Storytelling, voice novels download, modify available for bulk download)

labview做的分析语音信号的程序，做简单的频谱分析，识别(failed to translate)

在evmdm642平台下的一个语音采集-回放任务，用48K/秒的采样率采集立体声音频输入，用给定的FIR 滤波参数处理数据后再播放出来。注：内附个人整理的详细操作文档。(evmdm642 platform in a speech to the gathering-intervals task with 48 K/s sampling rate Acquisition stereo audio input, used to the FIR filter parameters for data processing later. Note : with a detailed personal finishing operations documentation.)

采用广义旁瓣抵消（GSC）自适应波束形成方法实现时域和频域滤波，采用LMS自适应算法，最终实现语音增强。（文件中包含纯净语音及不同信噪比的带噪语音）(Generalized sidelobe canceller (GSC) adaptive beamforming method to achieve time-domain filtering using the LMS adaptive algorithm, and ultimately the speech enhancement)

优化小波阈值，对硬阈值和软阈值的改进，通常用于语音信号增强，去噪(Optimization of wavelet threshold, the hard threshold and soft threshold improvement, commonly used in speech signal enhancement and denoise)

传统语音增强算法，谱减法和MCRC算法，matlab源代码。(Traditional speech enhancement algorithm, spectral subtraction and MCRC algorithm, matlab source code.)