• 【信号处理】Matlab实现CDR-based噪声和混响抑制


    1 内容介绍

    We investigate the estimation of the time- and frequency-dependent coherent-to-diffuse ratio (CDR) from the measured spatial coherence between two omnidirectional microphones. We illustrate the relationship between several known CDR estimators using a geometric interpretation in the complex plane, discuss the problem of estimator bias, and propose unbiased versions of the estimators. Furthermore, we show that knowledge of either the direction of arrival (DOA) of the target source or the coherence of the noise field is sufficient for an unbiased CDR estimation. Finally, we apply the CDR estimators to the problem of dereverberation, using automatic speech recognition word error rate as objective performance measure.

    2 部分代码

    %ESTIMATE_CDR_ROBUST_UNBIASED

    % Unbiased estimation of the Coherent-to-Diffuse Ratio (CDR) from the complex

    % coherence of a mixed (noisy) signal, using knowledge of both signal and noise

    % coherence. This is a variation of estimate_cdr_unbiased which shows better

    % performance in practice. Equivalent to CDRprop2 in [1].

    %

    % CDR = estimate_cdr_nodiffuse(X, N, S)

    %       X: complex coherence of mixed (noisy) signal

    %       N: coherence of noise component (real-valued)

    %       S: coherence of signal component (magnitude one)

    %

    % Reference:

    % Andreas Schwarz, Walter Kellermann, "Coherent-to-Diffuse Power Ratio

    % Estimation for Dereverberation", IEEE/ACM Trans. on Audio, Speech and

    % Lang. Proc., 2015 (under review); preprint available: arXiv:1502.03784

    % PDF: http://arxiv.org/pdf/1502.03784

    %

    % Andreas Schwarz (schwarz@lnt.de)

    % Multimedia Communications and Signal Processing

    % Friedrich-Alexander-Universitaet Erlangen-Nuernberg (FAU)

    % Cauerstr. 7, 91058 Erlangen, Germany

    function CDR = estimate_cdr_robust_unbiased(Cxx,Cnn,Css)

    Css = bsxfun(@times, ones(size(Cxx)), Css);

    Cnn = bsxfun(@times, ones(size(Cxx)), Cnn);

    % limit the magnitude of Cxx to prevent numerical problems

    magnitude_threshold = 1-1e-10;

    critical = abs(Cxx)>magnitude_threshold;

    Cxx(critical) = magnitude_threshold .* Cxx(critical) ./ abs(Cxx(critical));

    CDR = 1./(-abs(Cnn-exp(1j*angle(Css)))./(Cnn.*cos(angle(Css))-1)).*abs((exp(-1j*angle(Css)).*Cnn - (exp(-1i*angle(Css)).*Cxx))./(real(exp(-1i*angle(Css)).*Cxx) - 1));

    % Ensure we don't get any negative or complex results due to numerical effects

    CDR = max(real(CDR),0);

    end

    3 运行结果

    4 参考文献

    [1] Schwarz, A. , and  W. Kellermann . "Unbiased coherent-to-diffuse ratio estimation for dereverberation." International Workshop on Acoustic Signal Enhancement IEEE, 2014.

    博主简介:擅长智能优化算法神经网络预测信号处理元胞自动机图像处理路径规划无人机雷达通信无线传感器等多种领域的Matlab仿真,相关matlab代码问题可私信交流。

    部分理论引用网络文献,若有侵权联系博主删除。

     

  • 相关阅读:
    电网变电站安全作业行为规范检测-绝缘手套佩戴检测图像数据集(VOC,YOLO两类标签,六类目标)
    Java 一文详解二叉树的层序遍历
    2.6 Go语言中的Map
    【计算机网络-哈工大】---学习笔记(下)---(一)网络安全、密码学基础、对称、公钥、身份认证、数字签名、KDC\CA
    【小沐学C++】git和github常见问题汇总
    JasperReports做报表嵌套显示子报表显示不出来
    Raymarching(光线步进)基础
    quarkus依赖注入之七:生命周期回调
    CUDA/安装/win10
    PHP自动执行下一页脚本
  • 原文地址:https://blog.csdn.net/matlab_dingdang/article/details/126757121