搜索资源列表
fenxing
- 为提高语音端点检测(VAD)在较低信噪比(10 dB)下的准确率,提出一种基于短时分形维数的改进算法。结合语音信号的特点,对2种常用的语音信号分形维数计算方法进行了比较和选择,同时采用动态跟随门限值实现语音端点的自适应检测。试验结果表明:对于信噪比6~10 dB的带噪语音,此方法可以实现整段语音的检测,而且具有一定的噪声鲁棒性,系统运行期间能够自适应调整门限值以适应环境噪声的变化,提高了VAD算法的准确率。这个是源码matlab。-In order to improve voice activi
MmseCohen
- 利用I.Cohen提出的短时先验信噪比（priori SNR）估算的语音增强法，附有相应程序和文献。-I. Cohen raised by the use of short-term a priori signal to noise ratio (priori SNR) estimation of the speech enhancement method, with the corresponding procedures and documentation.
final
- 小波变换处理带噪语音信号，对于低信噪比的情况下相当有效，直接改文件名就可完成-Wavelet Transform of Noisy Speech signal processing for low SNR case quite effectively, direct to the file name can be completed
coleawin_Matlab_Speech_Analysis
- 波形和频谱双显示 记录讲话直接进入MATLAB 手动分割讲话波形-创建标签文件 波形编辑-切割，复制或粘贴 共振峰分析-显示共振轨道的F1 ， F2和F3 基音分析 过滤工具-语音信号滤波器截止频率 比较工具-比较两个波形的频谱距离使用几种措施 增加噪声-Dual time-waveform and spectrogram displays Records speech directly into MATLAB NEW Displays time-a
wavelet
- SPEECH ENHANCEMENT BASED ON WAVELET DENOISING Abstract: - Noise is an unwanted and inevitable interference in any form of communication. It is non-informative and plays the role of sucking the intelligence of the original signal. Any kind of
endpoint_detection_with_noise
- 提出了一种基于时频方差和的语音端点检测算法。实验证明该算法能够在低信噪比的情况下,准确地检测出语音信号-Proposed based on time-frequency variance and Speech Endpoint Detection Algorithm. Experiments show that the algorithm at low SNR cases, accurately detect the speech signal
noise_reduction_technique
- duction techniques proposed in the art are expressed as a spectral gain depending on the a priori SNR. In the well-known decision- directed approach, the a priori SNR depends on the speech spec- trum estimation in the previous frame. As a conse
2009101511335102
- 谱减法是一种比较简单的语音降噪的方法，在语音信号具有较高的信噪比的情况下具有良好的降噪功能。 -Spectral subtraction is a relatively simple pronunciation methods of noise in speech signal with high signal-to-noise ratio (SNR) of cases with good noise function.
snr
- 未加端点检测的说话认识别，带测试语音，可直接运行-Endpoint detection of speech does not increase understanding of other, with the test voice, can be directly run
zishiyingjiangzao
- 这里介绍了一种基于自适应滤波的噪声抵消法，采用归一化最小均方误差算法，采集实际噪声环境下各种不同信噪比的带噪语音样本进行降噪处理，实验结果表明，处理后信号的信噪比得到了较大程度的提高，大大改善了听音效果，具有很高的可懂度，且语音自然度好，没有失真；并与谱减法进行了比较，自适应噪声抵消法的降噪幅度比谱减法有一定提高，在听音效果上，用自适应噪声抵消法处理后的语音在清晰度，自然度方面优于谱减法。-Here a novel adaptive noise cancellation method using
testscript_intel
- voice) is the target signal and the second one (woman s voice) is the interfering speaker. To contrast the effects of an interference speaker (non-stationary noise) with a white noise inference (stationary noise/constant power) a white nois
fant.tar
- This tool can be used to - filter speech data with a frequency characteristic as defined by ITU for telephone equipment and/or - add noise to speech recordings at a desired SNR (signal-to-noise ratio)
idbm
- Descr iption Applies ideal binary mask to noise corrupted speech signal. The processing takes place within an FFT based short-time spectral analysis-modification-synthesis framework. The ideal binary mask is computed from an oracle (true) sign
relaxed-statistical-model-for-speech
- This file is about, Relaxed Statistical Model for Speech Enhancement and A Priori SNR Estimation
speech-recognition-system
- A robust speech recognit ion system based on discriminative learning of environmental features is proposed for recognit ion of environmental features in high noise background, and a g radient descent algo rithm was adopted for parameter
7102
- 基于匹配滤波器的语音识别。本程序接触匹配滤波对加噪语音进行匹配输出，使得信号的信噪比得到提升，送入后端DTW的语音识别系统，实验证明，本程序对语音提升有很大的帮助-A speech recoginiton base on the matched filter. this code will use matched filter and get speech SNR output enhanced. then we will extrace MFCC, send the feature to th
Desktop
- 单通道语音增强算法，利用logmmse来滤出噪声-speech enhancement by logmmse.we proved the speech SNR firstly
snr
- This MATLAB exercise computes and plots the SNR of a quantized speech file.
segmantal SNR
- 计算语音信号的信噪比和分段信噪比，在matlab中使用(Computing signal-to-noise ratio and segmentation SNR of speech signals are used in MATLAB)
longTermSNR.tar
- A CASA-Based System for Long-Term SNR Estimation