/// <summary>
/// 频域修正
/// </summary>
/// <param name="data1"></param>
/// <param name="begin1"></param>
/// <param name="end1"></param>
/// <param name="data2"></param>
/// <param name="begin2"></param>
/// <param name="end2"></param>
/// <returns></returns>
public static int[] MiddleFilterCorrection(int[] data1, int begin1, int end1, int[] data2, int begin2, int end2)
{
int[] res = new int[end1 - begin1];
int k = Math.Max(end1 - begin1, end2 - begin2);
int dx = FToneAnalysis.getmin2x(k);
//double dl = (double)NNAnalysis.samplingRate / dx;
double[] fftdata1 = new double[dx];
double[] fftdataimag1 = new double[dx];
Array.Copy(data1, begin1, fftdata1, 0, Math.Min(k, end1 - begin1));
TWFFT.FFT(fftdata1, fftdataimag1);
double[] fftdata2 = new double[dx];
double[] fftdataimag2 = new double[dx];
Array.Copy(data2, begin2, fftdata2, 0, Math.Min(k, end2 - begin2));
TWFFT.FFT(fftdata2, fftdataimag2);
int num = 15;
double[] lineori1 = new double[dx];
double[] lineori2 = new double[dx];
for (int i = 0; i < dx; i++)
{
lineori1[i] = Math.Abs(fftdata1[i]);
lineori2[i] = Math.Abs(fftdata2[i]);
//lineori1[i] = Math.Sqrt(Math.Pow(fftdata1[i], 2) + Math.Pow(fftdataimag1[i], 2));
//lineori2[i] = Math.Sqrt(Math.Pow(fftdata2[i], 2) + Math.Pow(fftdataimag2[i], 2));
}
double[] line1 = FToneAnalysis.MiddleFilter(lineori1, num);
//double[] linei1 = FToneAnalysis.MiddleFilter(fftdataimag1, num);
double[] line2 = FToneAnalysis.MiddleFilter(lineori2, num);
//double[] linei2 = FToneAnalysis.MiddleFilter(fftdataimag2, num);
for (int i = 0; i < line1.Length; i++)
{
//Complex c1 = new Complex(fftdata1[i], fftdataimag1[i]);
//Complex cl1 = new Complex(line1[i], linei1[i]);
//Complex cl2 = new Complex(line2[i], linei2[i]);
//c1 = c1.Multiply(cl1.Division(cl2));
fftdata1[i] = (int)((double)fftdata1[i] * (line2[i] / line1[i]));
//fftdataimag1[i] += (int)(linei2[i]-linei1[i]);
}
for (int i = dx / 4; i < dx / 2; i++)
{
if (line2[i] < line1[i])
{
fftdata1[i] = fftdata2[i];
fftdata1[dx - i] = fftdata2[dx - i];
}
}
TWFFT.IFFT(fftdata1, fftdataimag1);
for (int i = 0; i < res.Length; i++)
{
res[i] = (int)fftdata1[i];
}
return(res);
}
public static int[] getWAVdata(Bank tl, string tonename, double[][] pit, int length, double pitch)
{
//pit = getNewPit(pit, SemitoneTransfer.getTN( tl.sunit[tonename].pitch), pitch);
int[] oridata = tl.getTone(tonename);
oridata = FToneAnalysis.getSoundPart(oridata);
int newlen = (int)((double)length / 1000 * NBankManager.samplingRate);
int[] newdata = getChangeSoundTDPSOLA(oridata, pit, newlen);
return(newdata);
}
private static int[] getChangeSoundFDPSOLA(int[] oridata, double[][] zip, int tarlength)
{
int[] oricut = FToneAnalysis.cutIt(oridata);
int[] resdata = new int[tarlength];
int orilength = oridata.Length;
int[][] rescut = getCutPair(oricut, orilength, tarlength);
int overlaplen = 0;
for (int i = 0; i < rescut.Length; i++)
{
int oristart = rescut[i][0];
int tarstart = rescut[i][1];
int orilen = rescut[i][2];
int[] pitcdata = new int[orilen + overlaplen * 2];
double pitc = getZipValue(zip, (double)i * zip.Length / rescut.Length);
for (int j = 0; j < pitcdata.Length; j++)
{
int p = oristart + j - overlaplen;
if (p < 0 || p >= oridata.Length)
{
pitcdata[j] = 0;
}
else
{
pitcdata[j] = oridata[p];
}
}
pitcdata = ChangePitResutltFD(pitcdata, pitc);
for (int j = 0; j < orilen; j++)
{
int p = tarstart + j - overlaplen;
if (j < overlaplen && i != 0)
{
resdata[p] =
(int)(resdata[p] * (1 - (double)j / overlaplen)
+ pitcdata[j] * (double)j / overlaplen);
}
else if (p >= 0 && p < resdata.Length)
{
resdata[p] = pitcdata[j];
}
}
}
return(resdata);
}
/// <summary>
/// 用倒谱获得频谱包络
/// </summary>
/// <param name="data"></param>
/// <returns></returns>
private static double[] GetEnvelopeFD(double[] data)
{
int n = data.Length;
double[] data1 = new double[n];
double[] data1i = new double[n];
for (int i = 0; i < n; i++)
{
data1[i] = Math.Log(data[i]);
}
for (int i = 0; i < n; i++)
{
data1i[i] = 0;
}
TWFFT.FFT(data1, data1i);
double therehold = 100;
double[] data2 = new double[n];
double[] data2i = new double[n];
// 低通滤波
for (int i = 0; i < n; i++)
{
if (i < therehold || i > n - therehold)
{
data2[i] = data1[i];
data2i[i] = data1i[i];
}
else
{
data2[i] = 0;
data2i[i] = 0;
}
}
//for (int i = 0; i < n; i++) data2i[i] = 0;
TWFFT.IFFT(data2, data2i);
var res = FToneAnalysis.MiddleFilter(data2, 5);
for (int i = 0; i < n; i++)
{
res[i] = Math.Pow(Math.E, res[i]);
}
return(res);
}
private static int[] getChangeSoundUTAU(int[] oridata, double[][] zip, int tarlength)
{
int[] oricut = FToneAnalysis.cutIt(oridata);
int[] resdata = new int[tarlength];
int orilength = oridata.Length;
int[][] rescut = getCutPair(oricut, orilength, tarlength, zip);
int overlaplen = 0;
double k = (double)tarlength / orilength;
for (int i = 0; i < rescut.Length; i++)
{
int oristart = rescut[i][0];
int tarstart = rescut[i][1];
int orilen = rescut[i][2];
int[] pitcdata = new int[orilen + overlaplen * 2];
int laplen = orilen * 2;
int orilapstart = oristart - laplen / 2;
int tarlapstart = tarstart - laplen / 2;
int[] oriframe = new int[laplen];
for (int j = 0; j < laplen; j++)
{
if (orilapstart + j < 0 || orilapstart + j >= orilength)
{
oriframe[j] = 0;
}
else
{
oriframe[j] = oridata[orilapstart + j];
}
}
var oriframeh = Hanning(oriframe);
for (int j = 0; j < laplen; j++)
{
if (tarlapstart + j < 0 || tarlapstart + j >= tarlength)
{
continue;
}
else
{
resdata[tarlapstart + j] += oriframeh[j];
}
}
}
//int framelen = 4096;
//for(int i = 0; i < tarlength; i += framelen)
//{
// int[] od = new int[framelen];
// int[] td = new int[framelen];
// for(int j = 0; j < framelen; j++)
// {
// int d = (int)(i * k) + j;
// if (d >= oridata.Length) d = oridata.Length - framelen - 1 + j;
// od[j] = oridata[d];
// td[j] = resdata[i + j];
// }
//}
return(resdata);
}
/// <summary>
/// TD-PSOLA法合成
/// </summary>
/// <param name="oridata"></param>
/// <param name="zip"></param>
/// <param name="tarlength"></param>
/// <returns></returns>
private static int[] getChangeSoundTDPSOLA(int[] oridata, double[][] zip, int tarlength)
{
int[] oricut = FToneAnalysis.cutIt(oridata);
int[] resdata = new int[tarlength];
int orilength = oridata.Length;
int[][] rescut = getCutPair(oricut, orilength, tarlength, zip);
//int overlaplen = 20;
double k = (double)tarlength / orilength;
for (int i = 0; i < rescut.Length; i++)
{
int oristart = rescut[i][0];
int tarstart = rescut[i][1];
int orilen = rescut[i][2];
int laplen = orilen * 2;
int orilapstart = oristart - laplen / 2;
int tarlapstart = tarstart - laplen / 2;
int[] oriframe = new int[laplen];
for (int j = 0; j < laplen; j++)
{
if (orilapstart + j < 0 || orilapstart + j >= orilength)
{
oriframe[j] = 0;
}
else
{
oriframe[j] = oridata[orilapstart + j];
}
}
var oriframeh = Hanning(oriframe);
for (int j = 0; j < laplen; j++)
{
if (tarlapstart + j < 0 || tarlapstart + j >= tarlength)
{
continue;
}
else
{
resdata[tarlapstart + j] += oriframeh[j];
}
}
}
int[] resdata2 = new int[tarlength];
for (int i = 0; i < tarlength; i++)
{
resdata2[i] = 0;
}
int framelen = 1024;
for (int i = 0; i < tarlength; i += framelen / 2)
{
int[] od = new int[framelen];
int[] td = new int[framelen];
for (int j = 0; j < framelen; j++)
{
int d = (int)((double)i * orilength / tarlength) + j;
if (d >= oridata.Length)
{
d = oridata.Length - framelen - 1 + j;
}
if (i + j >= tarlength)
{
td[j] = 0; continue;
}
od[j] = oridata[d];
td[j] = resdata[i + j];
}
//od = Hanning(od);
//td = Hanning(td);
repairWaveShape(od, td);
//td = antiHanning(td);
for (int j = 0; j < framelen; j++)
{
int d = i + j;
if (d >= tarlength)
{
break;
}
if (j < framelen / 2)
{
resdata2[d] = (int)(resdata2[d] * (1 - (double)j * 2 / framelen) + td[j] * ((double)j * 2 / framelen));
}
else
{
resdata2[d] += td[j];
}
}
}
return(resdata);
//int framenum = cut.Length-1;
//// 获取逐帧频率压缩因子，用于接下来获取指定位置的压缩因子
//double[] framezip = getZipPoint(oridata.Length, zip);
//int[] res = new int[length];
////将开头段先放进去再说
////Array.Copy(oridata, 0, res, 0, Math.Min(length, cut[1]));
//int fbegin = cut[0];
//int fend = cut[1];
//double nowpos = 0;
//int respos = 0;
////对小段重采样
//int i = 1;
//while (i < framenum)
//{
// fbegin = cut[i - 1];
// fend = cut[i];
// int thislen = fend - fbegin;
// fbegin -= thislen / 2;
// fend += thislen / 2;
// double nowzip = 1 / Math.Max(framezip[Math.Max(fbegin, 0)], 0.1);
// //reset nowpos
// nowpos = fbegin;
// List<int> tmp = new List<int>();
// while (nowpos < fend)
// {
// int val = getResampleValue(oridata, nowpos);
// tmp.Add(val);
// nowpos += nowzip;
// }
// // 滤波
// int[] tmp2 = MiddleFilterCorrection( tmp.ToArray(), 0, tmp.Count, oridata, Math.Max(0,fbegin), fend);
// //tmp2 = FToneAnalysis.FrequencyFilter(tmp2, 0, 15000);
// // 用汉宁窗合并
// //var hanningtmp = tmp.ToArray();
// var hanningtmp = hanning(tmp2.ToArray());
// for (int j = 0; j < hanningtmp.Length; j++)
// {
// if (respos + j - cut[i - 1] + fbegin >= res.Length)
// {
// break;
// }
// else if (respos+j - cut[i - 1] + fbegin >= 0)
// {
// res[respos + j - cut[i - 1] + fbegin] += hanningtmp[j];
// //respos++;
// }
// }
// // 做中值平滑
// int width = thislen/2;
// int phstart = Math.Max(0, respos - width);
// int phlen = Math.Min(res.Length - phstart, width * 2);
// int[] phdata = new int[phlen];
// Array.Copy(res, phstart, phdata, 0, phlen);
// phdata = FToneAnalysis.MiddleFilter(phdata, 3);
// //phdata = FToneAnalysis.MiddleFilter(phdata, 5);
// Array.Copy(phdata, 0, res, phstart, phlen);
// respos += hanningtmp.Length / 2;
// i = getNearestFrameIndex(oridata.Length, length, cut, respos);
//}
//return res;
}
private static void repairWaveShape(int[] oridata, int[] tardata)
{
int n = FToneAnalysis.getmin2x(oridata.Length);
double[] odata = new double[n];
double[] odatai = new double[n];
for (int i = 0; i < n; i++)
{
if (i < oridata.Length)
{
odata[i] = oridata[i];
}
else
{
odata[i] = 0;
}
odatai[i] = 0;
}
TWFFT.FFT(odata, odatai);
double[] odatamod = new double[n];
for (int i = 0; i < n; i++)
{
odatamod[i] = Math.Sqrt(odata[i] * odata[i] + odatai[i] * odatai[i]);
}
var odataenv = GetEnvelopeFD(odatamod);
double[] tdata = new double[n];
double[] tdatai = new double[n];
for (int i = 0; i < n; i++)
{
if (i < tardata.Length)
{
tdata[i] = tardata[i];
}
else
{
tdata[i] = 0;
}
tdatai[i] = 0;
}
TWFFT.FFT(tdata, tdatai);
double[] tdatamod = new double[n];
for (int i = 0; i < n; i++)
{
tdatamod[i] = Math.Sqrt(tdata[i] * tdata[i] + tdatai[i] * tdatai[i]);
}
var tdataenv = GetEnvelopeFD(tdatamod);
for (int i = 1; i < n / 2; i++)
{
//if (odataenv[i] >= tdataenv[i]) continue;
tdata[i] = tdata[i] * (odataenv[i] / tdataenv[i]);
tdatai[i] = tdatai[i] * (odataenv[i] / tdataenv[i]);
tdata[n - i] = tdata[i];
tdatai[n - i] = tdatai[i];
}
TWFFT.IFFT(tdata, tdatai);
for (int i = 0; i < tardata.Length; i++)
{
tardata[i] = (int)tdata[i];
}
}
private static int[] ChangePitResutltFD(int[] data, double dpit)
{
// 傅里叶点数必须2的倍数
int n = FToneAnalysis.getmin2x(data.Length * 2);
n = 4096;
double[] ddata = new double[n];
for (int i = 0; i < n; i++)
{
if (i < data.Length)
{
ddata[i] = data[i];
}
else
{
ddata[i] = 0;
}
}
double[] ddatai = new double[n];
for (int i = 0; i < n; i++)
{
ddatai[i] = 0;
}
TWFFT.FFT(ddata, ddatai);
// ln(|X(n)|)
double[] ddatalnmod = new double[n];
for (int i = 0; i < n; i++)
{
ddatalnmod[i] = Math.Sqrt(ddata[i] * ddata[i] + ddatai[i] * ddatai[i]);
}
// 根据倒谱获取频谱包络，即声道滤波器
var ddataenv = GetEnvelopeFD(ddatalnmod);
// double[] ddataenv = new double[n];
//for (int i = 0; i < n; i++) ddataenv[i] = Math.Pow(Math.E, ddatalnenv[i]);
// 除以包络，得到激励谱
double[] ddatabase = new double[n];
double[] ddataibase = new double[n];
for (int i = 0; i < n; i++)
{
ddatabase[i] = ddata[i]; /// ddataenv[i];
}
for (int i = 0; i < n; i++)
{
ddataibase[i] = ddatai[i]; /// ddataenv[i];
}
// 拉伸激励谱，得到新基频下的激励谱
double[] ddatabaser = new double[n];
double[] ddataibaser = new double[n];
// 对称共轭，所以分两半分别压缩
ddatabaser[0] = ddatabase[0];
ddataibaser[0] = ddataibase[0];
//dpit = 1.4;
for (int i = 1; i < n / 2; i++)
{
int j = (int)(i - 3000 * (dpit - 1));
if (j < 1 || j >= n / 2)
{
ddatabaser[i] = 0;
ddataibaser[i] = 0;
}
else
{
ddatabaser[i] = ddatabase[j];
ddataibaser[i] = ddataibase[j];
}
ddatabaser[n - i] = ddatabaser[i];
ddataibaser[n - i] = -ddataibaser[i];
}
//for(int i = 1; i <= n/2; i++)
//{
// ddatabaser[i] = getResampleValue(ddatabase, (double)i / dpit);
// ddatabaser[n - i] = ddatabaser[i];
// ddataibaser[i] = getResampleValue(ddataibase, (double)i / dpit);
// ddataibaser[n - i] = -ddataibaser[i];
//}
// 激励谱与包络相乘，重建频谱
double[] ddatar = new double[n];
double[] ddatair = new double[n];
for (int i = 0; i < n; i++)
{
ddatar[i] = ddatabaser[i]; //* ddataenv[i];
}
for (int i = 0; i < n; i++)
{
ddatair[i] = ddataibaser[i]; //* ddataenv[i];
}
TWFFT.IFFT(ddatar, ddatair);
// int结果
int[] datar = new int[data.Length];
for (int i = 0; i < data.Length; i++)
{
datar[i] = (int)ddatar[i];
}
return(datar);
}
private static int[] getChangeSoundOld(int[] oridata, double[] pit, int length)
{
int[] res = new int[length];
int[] frame = FToneAnalysis.cutIt(oridata);
var zips = getZipPoint(length, pit);
//for (int i = 0; i < frame.Length; i++) frame[i] += cutbegin;
if (frame.Length == 0 || length < (int)(frame[0] * zips[0]))
{
// 目标长度小于第一个基音的长度，就不再合成，直接截断当作输出
double j = 0;
for (int i = 0; i < length; i++)
{
res[i] = oridata[(int)j];
j += zips[0];
}
}
else
{
//步长缩放因子
double scale = (double)oridata.Length / length;
int nowloc = 0;
while (nowloc < length)
{
int tmpnow = (int)(nowloc * scale);
int nextframe = getCRFrame(frame, tmpnow);
int framelen = getFrameLength(frame, nextframe);
if (nowloc > length - (oridata.Length - frame[frame.Length - 1]) / zips[nowloc])
{
//use the final frame (tail)
double j = 0;
double oldj = 0;
int stilltime = 1;
int stilltimenow = stilltime;
double olddelta = 1;
for (int i = 0; i < oridata.Length - frame[frame.Length - 1]; i++)
{
if (nowloc + (int)j >= length || frame[frame.Length - 1] + i >= oridata.Length)
{
break;
}
else
{
//interpolation
for (int s = (int)oldj; s < (int)j; s++)
{
if (nowloc + (int)s >= res.Length)
{
continue;
}
res[nowloc + (int)s] = oridata[frame[nextframe] - framelen + i];
}
double delta = 1 / zips[nowloc + (int)j];
if (delta > 100)
{
delta = 100;
}
oldj = j;
if (stilltimenow++ >= stilltime)
{
olddelta = delta;
stilltimenow = 0;
}
j += olddelta;
}
}
break;
}
else
{
//copy this frame
double j = 0;
double oldj = 0;
int stilltime = 1;
int stilltimenow = stilltime;
double olddelta = 1;
for (int i = 0; i < framelen; i++)
{
//interpolation
for (int s = (int)oldj; s < (int)j; s++)
{
if (nowloc + (int)s >= res.Length)
{
break;
}
res[nowloc + (int)s] = oridata[Math.Min(oridata.Length - 1, frame[nextframe] - framelen + i)];
}
if (nowloc + (int)j >= zips.Length)
{
continue;
}
double delta = 1 / zips[nowloc + (int)j];
if (delta > 100)
{
delta = 100;
}
oldj = j;
if (stilltimenow++ >= stilltime)
{
olddelta = delta;
stilltimenow = 0;
}
j += olddelta;
}
nowloc += (int)oldj;
}
}
}
////全局整形
//int[] newres = new int[res.Length];
//int dx = 1024;
//int nowx1 = 0;
//int nowx2 = 0;
//while (nowx1 < oridata.Length)
//{
// double[] data1 = new double[dx];
// double[] data2 = new double[dx];
// double[] dataimag1 = new double[dx];
// for (int i = 0; i < dx; i++) dataimag1[i] = 0;
// double[] dataimag2 = new double[dx];
// for (int i = 0; i < dx; i++) dataimag2[i] = 0;
// for (int i = 0; i < dx; i++)
// {
// data1[i] = nowx1 + i < oridata.Length ? oridata[nowx1 + i] : 0;
// data2[i] = nowx2 + i < res.Length ? (double)res[nowx2 + i] : 0;
// }
// TWFFT.FFT(data1, dataimag1);
// TWFFT.FFT(data2, dataimag2);
// double[] data1t = new double[dx];
// double[] data2t = new double[dx];
// for (int i = 0; i < dx; i++) data1t[i] = Math.Sqrt(data1[i] * data1[i] + dataimag1[i] * dataimag1[i]);
// for (int i = 0; i < dx; i++) data2t[i] = Math.Sqrt(data2[i] * data2[i] + dataimag2[i] * dataimag2[i]);
// int[,] envori = FormantAnalysis.getEnvelope3(data1t);
// int[,] env = FormantAnalysis.getEnvelope3(data2t);
// double[] envdelta = new double[env.GetLength(0)];
// //整形
// for (int i = 0; i < envdelta.Length; i++)
// {
// if (env[i, 1] == 0) envdelta[i] = 0;
// else envdelta[i] = (double)envori[i, 1] / env[i, 1];
// }
// for (int i = 1; i < envdelta.Length; i++)
// {
// for (int j = env[i - 1, 0]; j < env[i, 0]; j++)
// {
// data2[j] *= envdelta[i];
// dataimag2[j] *= envdelta[i];
// }
// }
// ////高通滤波
// //for (int i = 0; i < dx; i++)
// //{
// // if (data1t[i] < 1000)
// // {
// // data2[i] = data1[i];
// // dataimag2[i] = dataimag1[i];
// // }
// //}
//for (int i = (int)(dx/2 * rbegin); i < (int)(dx/2 * rend); i++)
//{
// data2[i] = 0;
// dataimag2[i] = 0;
//}
//for (int i = (int)(dx - dx / 2 * rbegin)-1; i >= (int)(dx - dx / 2 * rend); i--)
//{
// data2[i] = 0;
// dataimag2[i] = 0;
//}
// TWFFT.IFFT(data2, dataimag2);
// for (int i = 0; i < dx; i++)
// if (nowx2 + i < res.Length)
// newres[nowx2 + i] += (int)((double)data2[i] * (i < dx / 2 ? (double)i * 2.0 / dx : 2.0 - (double)(i) * 2.0 / dx));
// //newres[nowx2 + i] += (int)((double)data2[i] * Math.Sin(Math.PI * ((double)i / dx)));
// nowx2 += dx / 2;
// nowx1 += (int)((double)dx / 2 * oridata.Length / res.Length);
//}
//Array.Copy(newres, res, res.Length);
////填充空白
//for (int m = 0; m < 2; m++)
//{
// int t = 1 + m;
// for (int i = t; i < newlen - t; i++)
// {
// if (Math.Abs(res[i - t] * res[i + t]) > 100000 && res[i] < 20000)
// {
// res[i] = (res[i - t] + res[i + t]) / 2;
// }
// }
//}
//收尾
double percent = 0.1;
int num = (int)(length * percent);
//double scale = 1 / num;
for (int i = length - num; i < length; i++)
{
res[i] = (int)(res[i] * (double)(length - i) / num);
}
//for (int i = 0; i < newlen; i++)
//{
// if (Math.Abs(res[i]) <= 0)
// {
// res[i] = 0;
// }
//}
return(res);
}