private static void TestFFT(string title, kiss_fft_cpx<float>[] timeDomain, kiss_fft_cpx<float>[] frequencyDomain)
{
System.Console.WriteLine(title);
{ // FFT
KissFFT<float> kissFft = new KissFFT<float>(timeDomain.Length, false, new FloatArithmetic());
kissFft.kiss_fft(new Array<kiss_fft_cpx<float>>(timeDomain), new Array<kiss_fft_cpx<float>>(frequencyDomain));
for (int i = 0; i < frequencyDomain.Length; ++i)
{
frequencyDomain[i].r /= (float) frequencyDomain.Length;
frequencyDomain[i].i /= (float) frequencyDomain.Length;
}
System.Console.Write("Offset = {0} + {1} * i\n", frequencyDomain[0].r, frequencyDomain[0].i);
for (int i = 1; i < frequencyDomain.Length / 2 + 1; ++i)
{
System.Console.Write("f({0}): {1} + {2} * i, ", i, frequencyDomain[i].r * 2.0f, frequencyDomain[i].i * 2.0f);
PrintEuler(frequencyDomain[i].r * 2.0f, frequencyDomain[i].i * 2.0f);
System.Console.WriteLine();
}
}
{ // inverse FFT
kiss_fft_cpx<float>[] inverted = new kiss_fft_cpx<float>[frequencyDomain.Length];
KissFFT<float> kissFft = new KissFFT<float>(frequencyDomain.Length, true, new FloatArithmetic());
kissFft.kiss_fft(new Array<kiss_fft_cpx<float>>(frequencyDomain), new Array<kiss_fft_cpx<float>>(inverted));
for (int i = 0; i < frequencyDomain.Length; ++i)
{
const float treshold = 0.00001f;
if (!(Math.Abs(timeDomain[i].r - inverted[i].r) < treshold && Math.Abs(timeDomain[i].i - inverted[i].i) < treshold))
{
System.Console.Write("{0} ({1}, {2}) != ({3}, {4})\n", i, timeDomain[i].r, timeDomain[i].i, inverted[i].r, inverted[i].i);
}
}
System.Console.WriteLine();
}
}
private static void TestFFT(string title, kiss_fft_cpx <float>[] timeDomain, kiss_fft_cpx <float>[] frequencyDomain)
{
System.Console.WriteLine(title);
{ // FFT
KissFFT <float> kissFft = new KissFFT <float>(timeDomain.Length, false, new FloatArithmetic());
kissFft.kiss_fft(new Array <kiss_fft_cpx <float> >(timeDomain), new Array <kiss_fft_cpx <float> >(frequencyDomain));
for (int i = 0; i < frequencyDomain.Length; ++i)
{
frequencyDomain[i].r /= (float)frequencyDomain.Length;
frequencyDomain[i].i /= (float)frequencyDomain.Length;
}
System.Console.Write("Offset = {0} + {1} * i\n", frequencyDomain[0].r, frequencyDomain[0].i);
for (int i = 1; i < frequencyDomain.Length / 2 + 1; ++i)
{
System.Console.Write("f({0}): {1} + {2} * i, ", i, frequencyDomain[i].r * 2.0f, frequencyDomain[i].i * 2.0f);
PrintEuler(frequencyDomain[i].r * 2.0f, frequencyDomain[i].i * 2.0f);
System.Console.WriteLine();
}
}
{ // inverse FFT
kiss_fft_cpx <float>[] inverted = new kiss_fft_cpx <float> [frequencyDomain.Length];
KissFFT <float> kissFft = new KissFFT <float>(frequencyDomain.Length, true, new FloatArithmetic());
kissFft.kiss_fft(new Array <kiss_fft_cpx <float> >(frequencyDomain), new Array <kiss_fft_cpx <float> >(inverted));
for (int i = 0; i < frequencyDomain.Length; ++i)
{
const float treshold = 0.00001f;
if (!(Math.Abs(timeDomain[i].r - inverted[i].r) < treshold && Math.Abs(timeDomain[i].i - inverted[i].i) < treshold))
{
System.Console.Write("{0} ({1}, {2}) != ({3}, {4})\n", i, timeDomain[i].r, timeDomain[i].i, inverted[i].r, inverted[i].i);
}
}
System.Console.WriteLine();
}
}
/// <summary>
///
/// </summary>
/// <typeparam name="T">The type of signal being handled (either short or float) - changes based on which API is used</typeparam>
/// <param name="tonal"></param>
/// <param name="celt_mode"></param>
/// <param name="x"></param>
/// <param name="len"></param>
/// <param name="offset"></param>
/// <param name="c1"></param>
/// <param name="c2"></param>
/// <param name="C"></param>
/// <param name="lsb_depth"></param>
/// <param name="downmix"></param>
internal static void tonality_analysis <T>(TonalityAnalysisState tonal, CeltMode celt_mode, T[] x, int x_ptr, int len, int offset, int c1, int c2, int C, int lsb_depth, Downmix.downmix_func <T> downmix)
{
int i, b;
FFTState kfft;
int[] input;
int[] output;
int N = 480, N2 = 240;
float[] A = tonal.angle;
float[] dA = tonal.d_angle;
float[] d2A = tonal.d2_angle;
float[] tonality;
float[] noisiness;
float[] band_tonality = new float[OpusConstants.NB_TBANDS];
float[] logE = new float[OpusConstants.NB_TBANDS];
float[] BFCC = new float[8];
float[] features = new float[25];
float frame_tonality;
float max_frame_tonality;
/*float tw_sum=0;*/
float frame_noisiness;
float pi4 = (float)(M_PI * M_PI * M_PI * M_PI);
float slope = 0;
float frame_stationarity;
float relativeE;
float[] frame_probs = new float[2];
float alpha, alphaE, alphaE2;
float frame_loudness;
float bandwidth_mask;
int bandwidth = 0;
float maxE = 0;
float noise_floor;
int remaining;
AnalysisInfo info; //[porting note] pointer
tonal.last_transition++;
alpha = 1.0f / Inlines.IMIN(20, 1 + tonal.count);
alphaE = 1.0f / Inlines.IMIN(50, 1 + tonal.count);
alphaE2 = 1.0f / Inlines.IMIN(1000, 1 + tonal.count);
if (tonal.count < 4)
{
tonal.music_prob = 0.5f;
}
kfft = celt_mode.mdct.kfft[0];
if (tonal.count == 0)
{
tonal.mem_fill = 240;
}
downmix(x, x_ptr, tonal.inmem, tonal.mem_fill, Inlines.IMIN(len, OpusConstants.ANALYSIS_BUF_SIZE - tonal.mem_fill), offset, c1, c2, C);
if (tonal.mem_fill + len < OpusConstants.ANALYSIS_BUF_SIZE)
{
tonal.mem_fill += len;
/* Don't have enough to update the analysis */
return;
}
info = tonal.info[tonal.write_pos++];
if (tonal.write_pos >= OpusConstants.DETECT_SIZE)
{
tonal.write_pos -= OpusConstants.DETECT_SIZE;
}
input = new int[960];
output = new int[960];
tonality = new float[240];
noisiness = new float[240];
for (i = 0; i < N2; i++)
{
float w = Tables.analysis_window[i];
input[2 * i] = (int)(w * tonal.inmem[i]);
input[2 * i + 1] = (int)(w * tonal.inmem[N2 + i]);
input[(2 * (N - i - 1))] = (int)(w * tonal.inmem[N - i - 1]);
input[(2 * (N - i - 1)) + 1] = (int)(w * tonal.inmem[N + N2 - i - 1]);
}
Arrays.MemMoveInt(tonal.inmem, OpusConstants.ANALYSIS_BUF_SIZE - 240, 0, 240);
remaining = len - (OpusConstants.ANALYSIS_BUF_SIZE - tonal.mem_fill);
downmix(x, x_ptr, tonal.inmem, 240, remaining, offset + OpusConstants.ANALYSIS_BUF_SIZE - tonal.mem_fill, c1, c2, C);
tonal.mem_fill = 240 + remaining;
KissFFT.opus_fft(kfft, input, output);
for (i = 1; i < N2; i++)
{
float X1r, X2r, X1i, X2i;
float angle, d_angle, d2_angle;
float angle2, d_angle2, d2_angle2;
float mod1, mod2, avg_mod;
X1r = (float)output[2 * i] + output[2 * (N - i)];
X1i = (float)output[(2 * i) + 1] - output[2 * (N - i) + 1];
X2r = (float)output[(2 * i) + 1] + output[2 * (N - i) + 1];
X2i = (float)output[2 * (N - i)] - output[2 * i];
angle = (float)(.5f / M_PI) * fast_atan2f(X1i, X1r);
d_angle = angle - A[i];
d2_angle = d_angle - dA[i];
angle2 = (float)(.5f / M_PI) * fast_atan2f(X2i, X2r);
d_angle2 = angle2 - angle;
d2_angle2 = d_angle2 - d_angle;
mod1 = d2_angle - (float)Math.Floor(0.5f + d2_angle);
noisiness[i] = Inlines.ABS16(mod1);
mod1 *= mod1;
mod1 *= mod1;
mod2 = d2_angle2 - (float)Math.Floor(0.5f + d2_angle2);
noisiness[i] += Inlines.ABS16(mod2);
mod2 *= mod2;
mod2 *= mod2;
avg_mod = .25f * (d2A[i] + 2.0f * mod1 + mod2);
tonality[i] = 1.0f / (1.0f + 40.0f * 16.0f * pi4 * avg_mod) - .015f;
A[i] = angle2;
dA[i] = d_angle2;
d2A[i] = mod2;
}
frame_tonality = 0;
max_frame_tonality = 0;
/*tw_sum = 0;*/
info.activity = 0;
frame_noisiness = 0;
frame_stationarity = 0;
if (tonal.count == 0)
{
for (b = 0; b < OpusConstants.NB_TBANDS; b++)
{
tonal.lowE[b] = 1e10f;
tonal.highE[b] = -1e10f;
}
}
relativeE = 0;
frame_loudness = 0;
for (b = 0; b < OpusConstants.NB_TBANDS; b++)
{
float E = 0, tE = 0, nE = 0;
float L1, L2;
float stationarity;
for (i = Tables.tbands[b]; i < Tables.tbands[b + 1]; i++)
{
float binE = output[2 * i] * (float)output[2 * i] + output[2 * (N - i)] * (float)output[2 * (N - i)]
+ output[2 * i + 1] * (float)output[2 * i + 1] + output[2 * (N - i) + 1] * (float)output[2 * (N - i) + 1];
/* FIXME: It's probably best to change the BFCC filter initial state instead */
binE *= 5.55e-17f;
E += binE;
tE += binE * tonality[i];
nE += binE * 2.0f * (.5f - noisiness[i]);
}
tonal.E[tonal.E_count][b] = E;
frame_noisiness += nE / (1e-15f + E);
frame_loudness += (float)Math.Sqrt(E + 1e-10f);
logE[b] = (float)Math.Log(E + 1e-10f);
tonal.lowE[b] = Inlines.MIN32(logE[b], tonal.lowE[b] + 0.01f);
tonal.highE[b] = Inlines.MAX32(logE[b], tonal.highE[b] - 0.1f);
if (tonal.highE[b] < tonal.lowE[b] + 1.0f)
{
tonal.highE[b] += 0.5f;
tonal.lowE[b] -= 0.5f;
}
relativeE += (logE[b] - tonal.lowE[b]) / (1e-15f + tonal.highE[b] - tonal.lowE[b]);
L1 = L2 = 0;
for (i = 0; i < OpusConstants.NB_FRAMES; i++)
{
L1 += (float)Math.Sqrt(tonal.E[i][b]);
L2 += tonal.E[i][b];
}
stationarity = Inlines.MIN16(0.99f, L1 / (float)Math.Sqrt(1e-15 + OpusConstants.NB_FRAMES * L2));
stationarity *= stationarity;
stationarity *= stationarity;
frame_stationarity += stationarity;
/*band_tonality[b] = tE/(1e-15+E)*/
band_tonality[b] = Inlines.MAX16(tE / (1e-15f + E), stationarity * tonal.prev_band_tonality[b]);
frame_tonality += band_tonality[b];
if (b >= OpusConstants.NB_TBANDS - OpusConstants.NB_TONAL_SKIP_BANDS)
{
frame_tonality -= band_tonality[b - OpusConstants.NB_TBANDS + OpusConstants.NB_TONAL_SKIP_BANDS];
}
max_frame_tonality = Inlines.MAX16(max_frame_tonality, (1.0f + .03f * (b - OpusConstants.NB_TBANDS)) * frame_tonality);
slope += band_tonality[b] * (b - 8);
tonal.prev_band_tonality[b] = band_tonality[b];
}
bandwidth_mask = 0;
bandwidth = 0;
maxE = 0;
noise_floor = 5.7e-4f / (1 << (Inlines.IMAX(0, lsb_depth - 8)));
noise_floor *= 1 << (15 + CeltConstants.SIG_SHIFT);
noise_floor *= noise_floor;
for (b = 0; b < OpusConstants.NB_TOT_BANDS; b++)
{
float E = 0;
int band_start, band_end;
/* Keep a margin of 300 Hz for aliasing */
band_start = Tables.extra_bands[b];
band_end = Tables.extra_bands[b + 1];
for (i = band_start; i < band_end; i++)
{
float binE = output[2 * i] * (float)output[2 * i] + output[2 * (N - i)] * (float)output[2 * (N - i)]
+ output[2 * i + 1] * (float)output[2 * i + 1] + output[2 * (N - i) + 1] * (float)output[2 * (N - i) + 1];
E += binE;
}
maxE = Inlines.MAX32(maxE, E);
tonal.meanE[b] = Inlines.MAX32((1 - alphaE2) * tonal.meanE[b], E);
E = Inlines.MAX32(E, tonal.meanE[b]);
/* Use a simple follower with 13 dB/Bark slope for spreading function */
bandwidth_mask = Inlines.MAX32(.05f * bandwidth_mask, E);
/* Consider the band "active" only if all these conditions are met:
* 1) less than 10 dB below the simple follower
* 2) less than 90 dB below the peak band (maximal masking possible considering
* both the ATH and the loudness-dependent slope of the spreading function)
* 3) above the PCM quantization noise floor
*/
if (E > .1 * bandwidth_mask && E * 1e9f > maxE && E > noise_floor * (band_end - band_start))
{
bandwidth = b;
}
}
if (tonal.count <= 2)
{
bandwidth = 20;
}
frame_loudness = 20 * (float)Math.Log10(frame_loudness);
tonal.Etracker = Inlines.MAX32(tonal.Etracker - .03f, frame_loudness);
tonal.lowECount *= (1 - alphaE);
if (frame_loudness < tonal.Etracker - 30)
{
tonal.lowECount += alphaE;
}
for (i = 0; i < 8; i++)
{
float sum = 0;
for (b = 0; b < 16; b++)
{
sum += Tables.dct_table[i * 16 + b] * logE[b];
}
BFCC[i] = sum;
}
frame_stationarity /= OpusConstants.NB_TBANDS;
relativeE /= OpusConstants.NB_TBANDS;
if (tonal.count < 10)
{
relativeE = 0.5f;
}
frame_noisiness /= OpusConstants.NB_TBANDS;
info.activity = frame_noisiness + (1 - frame_noisiness) * relativeE;
frame_tonality = (max_frame_tonality / (OpusConstants.NB_TBANDS - OpusConstants.NB_TONAL_SKIP_BANDS));
frame_tonality = Inlines.MAX16(frame_tonality, tonal.prev_tonality * .8f);
tonal.prev_tonality = frame_tonality;
slope /= 8 * 8;
info.tonality_slope = slope;
tonal.E_count = (tonal.E_count + 1) % OpusConstants.NB_FRAMES;
tonal.count++;
info.tonality = frame_tonality;
for (i = 0; i < 4; i++)
{
features[i] = -0.12299f * (BFCC[i] + tonal.mem[i + 24]) + 0.49195f * (tonal.mem[i] + tonal.mem[i + 16]) + 0.69693f * tonal.mem[i + 8] - 1.4349f * tonal.cmean[i];
}
for (i = 0; i < 4; i++)
{
tonal.cmean[i] = (1 - alpha) * tonal.cmean[i] + alpha * BFCC[i];
}
for (i = 0; i < 4; i++)
{
features[4 + i] = 0.63246f * (BFCC[i] - tonal.mem[i + 24]) + 0.31623f * (tonal.mem[i] - tonal.mem[i + 16]);
}
for (i = 0; i < 3; i++)
{
features[8 + i] = 0.53452f * (BFCC[i] + tonal.mem[i + 24]) - 0.26726f * (tonal.mem[i] + tonal.mem[i + 16]) - 0.53452f * tonal.mem[i + 8];
}
if (tonal.count > 5)
{
for (i = 0; i < 9; i++)
{
tonal.std[i] = (1 - alpha) * tonal.std[i] + alpha * features[i] * features[i];
}
}
for (i = 0; i < 8; i++)
{
tonal.mem[i + 24] = tonal.mem[i + 16];
tonal.mem[i + 16] = tonal.mem[i + 8];
tonal.mem[i + 8] = tonal.mem[i];
tonal.mem[i] = BFCC[i];
}
for (i = 0; i < 9; i++)
{
features[11 + i] = (float)Math.Sqrt(tonal.std[i]);
}
features[20] = info.tonality;
features[21] = info.activity;
features[22] = frame_stationarity;
features[23] = info.tonality_slope;
features[24] = tonal.lowECount;
mlp.mlp_process(Tables.net, features, frame_probs);
frame_probs[0] = .5f * (frame_probs[0] + 1);
/* Curve fitting between the MLP probability and the actual probability */
frame_probs[0] = .01f + 1.21f * frame_probs[0] * frame_probs[0] - .23f * (float)Math.Pow(frame_probs[0], 10);
/* Probability of active audio (as opposed to silence) */
frame_probs[1] = .5f * frame_probs[1] + .5f;
/* Consider that silence has a 50-50 probability. */
frame_probs[0] = frame_probs[1] * frame_probs[0] + (1 - frame_probs[1]) * .5f;
/*printf("%f %f ", frame_probs[0], frame_probs[1]);*/
{
/* Probability of state transition */
float tau;
/* Represents independence of the MLP probabilities, where
* beta=1 means fully independent. */
float beta;
/* Denormalized probability of speech (p0) and music (p1) after update */
float p0, p1;
/* Probabilities for "all speech" and "all music" */
float s0, m0;
/* Probability sum for renormalisation */
float psum;
/* Instantaneous probability of speech and music, with beta pre-applied. */
float speech0;
float music0;
/* One transition every 3 minutes of active audio */
tau = .00005f * frame_probs[1];
beta = .05f;
//if (1)
{
/* Adapt beta based on how "unexpected" the new prob is */
float p, q;
p = Inlines.MAX16(.05f, Inlines.MIN16(.95f, frame_probs[0]));
q = Inlines.MAX16(.05f, Inlines.MIN16(.95f, tonal.music_prob));
beta = .01f + .05f * Inlines.ABS16(p - q) / (p * (1 - q) + q * (1 - p));
}
/* p0 and p1 are the probabilities of speech and music at this frame
* using only information from previous frame and applying the
* state transition model */
p0 = (1 - tonal.music_prob) * (1 - tau) + tonal.music_prob * tau;
p1 = tonal.music_prob * (1 - tau) + (1 - tonal.music_prob) * tau;
/* We apply the current probability with exponent beta to work around
* the fact that the probability estimates aren't independent. */
p0 *= (float)Math.Pow(1 - frame_probs[0], beta);
p1 *= (float)Math.Pow(frame_probs[0], beta);
/* Normalise the probabilities to get the Marokv probability of music. */
tonal.music_prob = p1 / (p0 + p1);
info.music_prob = tonal.music_prob;
/* This chunk of code deals with delayed decision. */
psum = 1e-20f;
/* Instantaneous probability of speech and music, with beta pre-applied. */
speech0 = (float)Math.Pow(1 - frame_probs[0], beta);
music0 = (float)Math.Pow(frame_probs[0], beta);
if (tonal.count == 1)
{
tonal.pspeech[0] = 0.5f;
tonal.pmusic[0] = 0.5f;
}
/* Updated probability of having only speech (s0) or only music (m0),
* before considering the new observation. */
s0 = tonal.pspeech[0] + tonal.pspeech[1];
m0 = tonal.pmusic[0] + tonal.pmusic[1];
/* Updates s0 and m0 with instantaneous probability. */
tonal.pspeech[0] = s0 * (1 - tau) * speech0;
tonal.pmusic[0] = m0 * (1 - tau) * music0;
/* Propagate the transition probabilities */
for (i = 1; i < OpusConstants.DETECT_SIZE - 1; i++)
{
tonal.pspeech[i] = tonal.pspeech[i + 1] * speech0;
tonal.pmusic[i] = tonal.pmusic[i + 1] * music0;
}
/* Probability that the latest frame is speech, when all the previous ones were music. */
tonal.pspeech[OpusConstants.DETECT_SIZE - 1] = m0 * tau * speech0;
/* Probability that the latest frame is music, when all the previous ones were speech. */
tonal.pmusic[OpusConstants.DETECT_SIZE - 1] = s0 * tau * music0;
/* Renormalise probabilities to 1 */
for (i = 0; i < OpusConstants.DETECT_SIZE; i++)
{
psum += tonal.pspeech[i] + tonal.pmusic[i];
}
psum = 1.0f / psum;
for (i = 0; i < OpusConstants.DETECT_SIZE; i++)
{
tonal.pspeech[i] *= psum;
tonal.pmusic[i] *= psum;
}
psum = tonal.pmusic[0];
for (i = 1; i < OpusConstants.DETECT_SIZE; i++)
{
psum += tonal.pspeech[i];
}
/* Estimate our confidence in the speech/music decisions */
if (frame_probs[1] > .75)
{
if (tonal.music_prob > .9)
{
float adapt;
adapt = 1.0f / (++tonal.music_confidence_count);
tonal.music_confidence_count = Inlines.IMIN(tonal.music_confidence_count, 500);
tonal.music_confidence += adapt * Inlines.MAX16(-.2f, frame_probs[0] - tonal.music_confidence);
}
if (tonal.music_prob < .1)
{
float adapt;
adapt = 1.0f / (++tonal.speech_confidence_count);
tonal.speech_confidence_count = Inlines.IMIN(tonal.speech_confidence_count, 500);
tonal.speech_confidence += adapt * Inlines.MIN16(.2f, frame_probs[0] - tonal.speech_confidence);
}
}
else
{
if (tonal.music_confidence_count == 0)
{
tonal.music_confidence = .9f;
}
if (tonal.speech_confidence_count == 0)
{
tonal.speech_confidence = .1f;
}
}
}
if (tonal.last_music != ((tonal.music_prob > .5f) ? 1 : 0))
{
tonal.last_transition = 0;
}
tonal.last_music = (tonal.music_prob > .5f) ? 1 : 0;
info.bandwidth = bandwidth;
info.noisiness = frame_noisiness;
info.valid = 1;
}
