//matchfile 是数据库里取出的，注册声音的输出结果（txt文件）
//inputfile是测试时输入的声音，outputfile是输出文件
//这个函数算出来的是【单个】测试声音和数据库里保存声音【处理后的】文件的距离的平均值，然后算出的匹配度。
public static double matchingDegree(String[] matchfile, String inputfile, String outputfile)
{
//这个是getMfcc的重载函数，Register.cs里用的是字符串数组为参数，这里是单个字符串为参数。
MFCC.getMfcc(inputfile, outputfile);
int len = matchfile.Length;
double distance = Dtw.getDtw(matchfile[0], outputfile);
for (int i = 1; i < len; i++)
{
distance = distance + Dtw.getDtw(matchfile[i], outputfile);
}
distance = distance / len / 1.0;
var credit = ((50 - distance) / 50.0) * 100;
if (credit < 80)
{
credit = 0;
}
else if (credit > 100)
{
credit = 100;
}
else
{
credit = Math.Sqrt((credit - 80) / 20);
}
credit *= 100;
return(credit);
}
protected double[,] dtwpath = new double[DTWMAXNUM, DTWMAXNUM]; /*保存路径*/
public static double getDtw(String file1, String file2)
{
//定义2个数组a_d
double[] a_data = new double[] {
0.0, 0.2, 0.4,
0.3, 0.2, 0.4,
0.4, 0.2, 0.4,
0.5, 0.2, 0.4,
5.0, 5.2, 8.4,
6.0, 5.2, 7.4,
4.0, 5.2, 4.4,
10.3, 10.4, 10.5,
10.1, 10.6, 10.7,
11.3, 10.2, 10.9
};
double[] b_data = new double[] {
0.1, 0.2, 0.4,
0.3, 0.2, 0.4,
0.4, 0.2, 0.4,
0.5, 0.2, 0.4,
5.0, 5.2, 8.4,
6.0, 5.2, 7.4,
4.0, 5.2, 4.4,
10.3, 10.4, 10.5,
10.1, 10.6, 10.7,
11.3, 10.2, 10.9
};
Dtw dtw = new Dtw();
//读mfcc数据文件到数组
int i = 0, j = 0, r;
double[] a = null;
double[] b = null;
a = dtw.read_file(file1, ref i);
if (a == null)
{
//Console.Write("error!\n");
return(-1);
}
b = dtw.read_file(file2, ref j);
if (b == null)
{
//Console.Write("error!\n");
return(-1);
}
//Console.Write("i = " + i + "\n");
//Console.Write("j = " + j + "\n");
double ret1, ret2;
r = Math.Min(i, j) / 30;
//ret=DTWDistanceFun(a_data, 10, b_data, 10, 2);
ret1 = dtw.DTWDistanceFun(a, i, b, j, r);
//Console.Write("DTW distance = " + ret1 + "\n");
// ret2 = dtw.DTWDistanceFun(b, j, a, i, r);
//Console.Write("DTW distance = " + ret2 + "\n");
//mvector av, bv;
//ret=VDTWDistanceFun(a_data, 10, b_data, 10, 2);
//printf("VDTW distance :%f\n", ret);
return(ret1);
}
