基音变化率4.txt

各种SVM分类算法

clear all
for h=1:20
fname=sprintf('D:\\study\\音频采样\\noise22050hz\\%d.wav',h);
x=wavread(fname);
x=x(:,1);
[c,l]=wavedec(x,3,'db4');
ca=appcoef(c,l,'db4',3);%近似系数
x=ca;
enframex=enframe(x,128,64);%对信号x分帧处理，每帧有128个采样点，相邻帧之间有50%的叠加率
[row,col]=size(enframex);%返回行，列，每一行代表一帧，每一列表示1到128个采样点

framelen=col;
frameinc=64;  
hang=row;%计算出分帧后语音矩阵的行数
temp1=enframe(x,framelen,frameinc);%将分帧后的数据存入temp1数组矩阵
for i=1:hang;
 j=1:frameinc;
    z(i)=max(temp1(i,j));%求第i帧前frameinc个元素最大值并存入z(i)数组中
end
for i=1:hang;
 j=framelen-frameinc:framelen;
    a(i)=max(temp1(i,j));
end
i=1:hang;
c(i)=min(z(i),a(i))*0.68;%计算每帧的门限值
for i=1:hang;
 for j=1:framelen;
    if temp1(i,j)>c(i)
        y(i,j)=temp1(i,j)-c(i);
    else if abs(temp1(i,j))<=c(i)
            y(i,j)=0;
        else if temp1(i,j)<c(i)*(-1)
                y(i,j)=temp1(i,j)+c(i);
            end 
        end
    end
 end
end
for i=1:hang;
if (j>=0)&(j<=20)
    y(i,j)=0;
end
end   %将0到20点置零
for i=1:hang;
   for j=framelen:450;
       y(i,j)=0;  %将framelen点到450点的值置零
       
   end
end
    
for i=1:hang;
   for j=1:framelen;
    if y(i,j)>0
        y1(i,j)=1;
    else if y(i,j)==0;
            y1(i,j)=0;
        else if y(i,j)<0
                y1(i,j)=-1;
            end
        end
    end
end
end
for i=1:hang;
if (j>=0)&(j<=20)
    y1(i,j)=0;
end
end   %将0到20点置零
for i=1:hang;
   for j=framelen:450;
       y1(i,j)=0;  %将framelen点到450点的值置零
   end
end
       
       
for i=1:hang;
    for k=1:128;
    n=21:framelen;
    R(i,k)=sum(y(i,n).*y1(i,n+k));
end
end
%计算每一帧y与y1的互相关值
for i=1:hang;
    k=20:128;
Rmax(i)=max(R(i,k));%计算每帧的Rmax值
end
for i=1:hang;
    k=20:128;
    [r,kmax(i)]=max(R(i,k));%找出每帧Rmax对应的k值kmax
end
  
for i=1:hang;
    if Rmax(i)<0.25*R(i,1)
        P(i)=0;
    else P(i)=1/kmax(i);
    end
end

a=0;
for i=1:(hang-1);
    a=a+abs(P(i+1)-P(i));
end
noisebianhualv(h)=a/framelen;
end
noisebianhualv'