Пример #1
0
void tonality_analysis(TonalityAnalysisState *tonal, AnalysisInfo *info_out, const CELTMode *celt_mode, const void *x, int len, int offset, int c1, int c2, int C, int lsb_depth, downmix_func downmix)
{
    int i, b;
    const kiss_fft_state *kfft;
    VARDECL(kiss_fft_cpx, in);
    VARDECL(kiss_fft_cpx, out);
    int N = 480, N2=240;
    float * OPUS_RESTRICT A = tonal->angle;
    float * OPUS_RESTRICT dA = tonal->d_angle;
    float * OPUS_RESTRICT d2A = tonal->d2_angle;
    VARDECL(float, tonality);
    VARDECL(float, noisiness);
    float band_tonality[NB_TBANDS];
    float logE[NB_TBANDS];
    float BFCC[8];
    float features[25];
    float frame_tonality;
    float max_frame_tonality;
    /*float tw_sum=0;*/
    float frame_noisiness;
    const float pi4 = (float)(M_PI*M_PI*M_PI*M_PI);
    float slope=0;
    float frame_stationarity;
    float relativeE;
    float frame_probs[2];
    float alpha, alphaE, alphaE2;
    float frame_loudness;
    float bandwidth_mask;
    int bandwidth=0;
    float maxE = 0;
    float noise_floor;
    int remaining;
    AnalysisInfo *info;
    SAVE_STACK;

    tonal->last_transition++;
    alpha = 1.f/IMIN(20, 1+tonal->count);
    alphaE = 1.f/IMIN(50, 1+tonal->count);
    alphaE2 = 1.f/IMIN(1000, 1+tonal->count);

    if (tonal->count<4)
       tonal->music_prob = .5;
    kfft = celt_mode->mdct.kfft[0];
    if (tonal->count==0)
       tonal->mem_fill = 240;
    downmix(x, &tonal->inmem[tonal->mem_fill], IMIN(len, ANALYSIS_BUF_SIZE-tonal->mem_fill), offset, c1, c2, C);
    if (tonal->mem_fill+len < ANALYSIS_BUF_SIZE)
    {
       tonal->mem_fill += len;
       /* Don't have enough to update the analysis */
       RESTORE_STACK;
       return;
    }
    info = &tonal->info[tonal->write_pos++];
    if (tonal->write_pos>=DETECT_SIZE)
       tonal->write_pos-=DETECT_SIZE;

    ALLOC(in, 480, kiss_fft_cpx);
    ALLOC(out, 480, kiss_fft_cpx);
    ALLOC(tonality, 240, float);
    ALLOC(noisiness, 240, float);
    for (i=0;i<N2;i++)
    {
       float w = analysis_window[i];
       in[i].r = (kiss_fft_scalar)(w*tonal->inmem[i]);
       in[i].i = (kiss_fft_scalar)(w*tonal->inmem[N2+i]);
       in[N-i-1].r = (kiss_fft_scalar)(w*tonal->inmem[N-i-1]);
       in[N-i-1].i = (kiss_fft_scalar)(w*tonal->inmem[N+N2-i-1]);
    }
    OPUS_MOVE(tonal->inmem, tonal->inmem+ANALYSIS_BUF_SIZE-240, 240);
    remaining = len - (ANALYSIS_BUF_SIZE-tonal->mem_fill);
    downmix(x, &tonal->inmem[240], remaining, offset+ANALYSIS_BUF_SIZE-tonal->mem_fill, c1, c2, C);
    tonal->mem_fill = 240 + remaining;
    opus_fft(kfft, in, out);

    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)out[i].r+out[N-i].r;
       X1i = (float)out[i].i-out[N-i].i;
       X2r = (float)out[i].i+out[N-i].i;
       X2i = (float)out[N-i].r-out[i].r;

       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)floor(.5+d2_angle);
       noisiness[i] = ABS16(mod1);
       mod1 *= mod1;
       mod1 *= mod1;

       mod2 = d2_angle2 - (float)floor(.5+d2_angle2);
       noisiness[i] += ABS16(mod2);
       mod2 *= mod2;
       mod2 *= mod2;

       avg_mod = .25f*(d2A[i]+2.f*mod1+mod2);
       tonality[i] = 1.f/(1.f+40.f*16.f*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)
    {
       for (b=0;b<NB_TBANDS;b++)
       {
          tonal->lowE[b] = 1e10;
          tonal->highE[b] = -1e10;
       }
    }
    relativeE = 0;
    frame_loudness = 0;
    for (b=0;b<NB_TBANDS;b++)
    {
       float E=0, tE=0, nE=0;
       float L1, L2;
       float stationarity;
       for (i=tbands[b];i<tbands[b+1];i++)
       {
          float binE = out[i].r*(float)out[i].r + out[N-i].r*(float)out[N-i].r
                     + out[i].i*(float)out[i].i + out[N-i].i*(float)out[N-i].i;
#ifdef FIXED_POINT
          /* FIXME: It's probably best to change the BFCC filter initial state instead */
          binE *= 5.55e-17f;
#endif
          E += binE;
          tE += binE*tonality[i];
          nE += binE*2.f*(.5f-noisiness[i]);
       }
       tonal->E[tonal->E_count][b] = E;
       frame_noisiness += nE/(1e-15f+E);

       frame_loudness += (float)sqrt(E+1e-10f);
       logE[b] = (float)log(E+1e-10f);
       tonal->lowE[b] = MIN32(logE[b], tonal->lowE[b]+.01f);
       tonal->highE[b] = MAX32(logE[b], tonal->highE[b]-.1f);
       if (tonal->highE[b] < tonal->lowE[b]+1.f)
       {
          tonal->highE[b]+=.5f;
          tonal->lowE[b]-=.5f;
       }
       relativeE += (logE[b]-tonal->lowE[b])/(1e-15f+tonal->highE[b]-tonal->lowE[b]);

       L1=L2=0;
       for (i=0;i<NB_FRAMES;i++)
       {
          L1 += (float)sqrt(tonal->E[i][b]);
          L2 += tonal->E[i][b];
       }

       stationarity = MIN16(0.99f,L1/(float)sqrt(1e-15+NB_FRAMES*L2));
       stationarity *= stationarity;
       stationarity *= stationarity;
       frame_stationarity += stationarity;
       /*band_tonality[b] = tE/(1e-15+E)*/;
       band_tonality[b] = MAX16(tE/(1e-15f+E), stationarity*tonal->prev_band_tonality[b]);
#if 0
       if (b>=NB_TONAL_SKIP_BANDS)
       {
          frame_tonality += tweight[b]*band_tonality[b];
          tw_sum += tweight[b];
       }
#else
       frame_tonality += band_tonality[b];
       if (b>=NB_TBANDS-NB_TONAL_SKIP_BANDS)
          frame_tonality -= band_tonality[b-NB_TBANDS+NB_TONAL_SKIP_BANDS];
#endif
       max_frame_tonality = MAX16(max_frame_tonality, (1.f+.03f*(b-NB_TBANDS))*frame_tonality);
       slope += band_tonality[b]*(b-8);
       /*printf("%f %f ", band_tonality[b], stationarity);*/
       tonal->prev_band_tonality[b] = band_tonality[b];
    }

    bandwidth_mask = 0;
    bandwidth = 0;
    maxE = 0;
    noise_floor = 5.7e-4f/(1<<(IMAX(0,lsb_depth-8)));
#ifdef FIXED_POINT
    noise_floor *= 1<<(15+SIG_SHIFT);
#endif
    noise_floor *= noise_floor;
    for (b=0;b<NB_TOT_BANDS;b++)
    {
       float E=0;
       int band_start, band_end;
       /* Keep a margin of 300 Hz for aliasing */
       band_start = extra_bands[b];
       band_end = extra_bands[b+1];
       for (i=band_start;i<band_end;i++)
       {
          float binE = out[i].r*(float)out[i].r + out[N-i].r*(float)out[N-i].r
                     + out[i].i*(float)out[i].i + out[N-i].i*(float)out[N-i].i;
          E += binE;
       }
       maxE = MAX32(maxE, E);
       tonal->meanE[b] = MAX32((1-alphaE2)*tonal->meanE[b], E);
       E = MAX32(E, tonal->meanE[b]);
       /* Use a simple follower with 13 dB/Bark slope for spreading function */
       bandwidth_mask = 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)log10(frame_loudness);
    tonal->Etracker = 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 += dct_table[i*16+b]*logE[b];
       BFCC[i] = sum;
    }

    frame_stationarity /= NB_TBANDS;
    relativeE /= NB_TBANDS;
    if (tonal->count<10)
       relativeE = .5;
    frame_noisiness /= NB_TBANDS;
#if 1
    info->activity = frame_noisiness + (1-frame_noisiness)*relativeE;
#else
    info->activity = .5*(1+frame_noisiness-frame_stationarity);
#endif
    frame_tonality = (max_frame_tonality/(NB_TBANDS-NB_TONAL_SKIP_BANDS));
    frame_tonality = 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)%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)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;

#ifndef DISABLE_FLOAT_API
    mlp_process(&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)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 = MAX16(.05f,MIN16(.95f,frame_probs[0]));
          q = MAX16(.05f,MIN16(.95f,tonal->music_prob));
          beta = .01f+.05f*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)pow(1-frame_probs[0], beta);
       p1 *= (float)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)pow(1-frame_probs[0], beta);
       music0  = (float)pow(frame_probs[0], beta);
       if (tonal->count==1)
       {
          tonal->pspeech[0]=.5;
          tonal->pmusic [0]=.5;
       }
       /* 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<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[DETECT_SIZE-1] = m0*tau*speech0;
       /* Probability that the latest frame is music, when all the previous ones were speech. */
       tonal->pmusic [DETECT_SIZE-1] = s0*tau*music0;

       /* Renormalise probabilities to 1 */
       for (i=0;i<DETECT_SIZE;i++)
          psum += tonal->pspeech[i] + tonal->pmusic[i];
       psum = 1.f/psum;
       for (i=0;i<DETECT_SIZE;i++)
       {
          tonal->pspeech[i] *= psum;
          tonal->pmusic [i] *= psum;
       }
       psum = tonal->pmusic[0];
       for (i=1;i<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.f/(++tonal->music_confidence_count);
             tonal->music_confidence_count = IMIN(tonal->music_confidence_count, 500);
             tonal->music_confidence += adapt*MAX16(-.2f,frame_probs[0]-tonal->music_confidence);
          }
          if (tonal->music_prob<.1)
          {
             float adapt;
             adapt = 1.f/(++tonal->speech_confidence_count);
             tonal->speech_confidence_count = IMIN(tonal->speech_confidence_count, 500);
             tonal->speech_confidence += adapt*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))
       tonal->last_transition=0;
    tonal->last_music = tonal->music_prob>.5f;
#else
    info->music_prob = 0;
#endif
    /*for (i=0;i<25;i++)
       printf("%f ", features[i]);
    printf("\n");*/

    info->bandwidth = bandwidth;
    /*printf("%d %d\n", info->bandwidth, info->opus_bandwidth);*/
    info->noisiness = frame_noisiness;
    info->valid = 1;
    if (info_out!=NULL)
       OPUS_COPY(info_out, info, 1);
    RESTORE_STACK;
}
Пример #2
0
static void tonality_analysis(TonalityAnalysisState *tonal, const CELTMode *celt_mode, const void *x, int len, int offset, int c1, int c2, int C, int lsb_depth, downmix_func downmix)
{
    int i, b;
    const kiss_fft_state *kfft;
    VARDECL(kiss_fft_cpx, in);
    VARDECL(kiss_fft_cpx, out);
    int N = 480, N2=240;
    float * OPUS_RESTRICT A = tonal->angle;
    float * OPUS_RESTRICT dA = tonal->d_angle;
    float * OPUS_RESTRICT d2A = tonal->d2_angle;
    VARDECL(float, tonality);
    VARDECL(float, noisiness);
    float band_tonality[NB_TBANDS];
    float logE[NB_TBANDS];
    float BFCC[8];
    float features[25];
    float frame_tonality;
    float max_frame_tonality;
    /*float tw_sum=0;*/
    float frame_noisiness;
    const float pi4 = (float)(M_PI*M_PI*M_PI*M_PI);
    float slope=0;
    float frame_stationarity;
    float relativeE;
    float frame_probs[2];
    float alpha, alphaE, alphaE2;
    float frame_loudness;
    float bandwidth_mask;
    int bandwidth=0;
    float maxE = 0;
    float noise_floor;
    int remaining;
    AnalysisInfo *info;
    float hp_ener;
    float tonality2[240];
    float midE[8];
    float spec_variability=0;
    float band_log2[NB_TBANDS+1];
    float leakage_from[NB_TBANDS+1];
    float leakage_to[NB_TBANDS+1];
    SAVE_STACK;

    alpha = 1.f/IMIN(10, 1+tonal->count);
    alphaE = 1.f/IMIN(25, 1+tonal->count);
    alphaE2 = 1.f/IMIN(500, 1+tonal->count);

    if (tonal->Fs == 48000)
    {
       /* len and offset are now at 24 kHz. */
       len/= 2;
       offset /= 2;
    } else if (tonal->Fs == 16000) {
       len = 3*len/2;
       offset = 3*offset/2;
    }

    if (tonal->count<4) {
       if (tonal->application == OPUS_APPLICATION_VOIP)
          tonal->music_prob = .1f;
       else
          tonal->music_prob = .625f;
    }
    kfft = celt_mode->mdct.kfft[0];
    if (tonal->count==0)
       tonal->mem_fill = 240;
    tonal->hp_ener_accum += (float)downmix_and_resample(downmix, x,
          &tonal->inmem[tonal->mem_fill], tonal->downmix_state,
          IMIN(len, ANALYSIS_BUF_SIZE-tonal->mem_fill), offset, c1, c2, C, tonal->Fs);
    if (tonal->mem_fill+len < ANALYSIS_BUF_SIZE)
    {
       tonal->mem_fill += len;
       /* Don't have enough to update the analysis */
       RESTORE_STACK;
       return;
    }
    hp_ener = tonal->hp_ener_accum;
    info = &tonal->info[tonal->write_pos++];
    if (tonal->write_pos>=DETECT_SIZE)
       tonal->write_pos-=DETECT_SIZE;

    ALLOC(in, 480, kiss_fft_cpx);
    ALLOC(out, 480, kiss_fft_cpx);
    ALLOC(tonality, 240, float);
    ALLOC(noisiness, 240, float);
    for (i=0;i<N2;i++)
    {
       float w = analysis_window[i];
       in[i].r = (kiss_fft_scalar)(w*tonal->inmem[i]);
       in[i].i = (kiss_fft_scalar)(w*tonal->inmem[N2+i]);
       in[N-i-1].r = (kiss_fft_scalar)(w*tonal->inmem[N-i-1]);
       in[N-i-1].i = (kiss_fft_scalar)(w*tonal->inmem[N+N2-i-1]);
    }
    OPUS_MOVE(tonal->inmem, tonal->inmem+ANALYSIS_BUF_SIZE-240, 240);
    remaining = len - (ANALYSIS_BUF_SIZE-tonal->mem_fill);
    tonal->hp_ener_accum = (float)downmix_and_resample(downmix, x,
          &tonal->inmem[240], tonal->downmix_state, remaining,
          offset+ANALYSIS_BUF_SIZE-tonal->mem_fill, c1, c2, C, tonal->Fs);
    tonal->mem_fill = 240 + remaining;
    opus_fft(kfft, in, out, tonal->arch);
#ifndef FIXED_POINT
    /* If there's any NaN on the input, the entire output will be NaN, so we only need to check one value. */
    if (celt_isnan(out[0].r))
    {
       info->valid = 0;
       RESTORE_STACK;
       return;
    }
#endif

    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)out[i].r+out[N-i].r;
       X1i = (float)out[i].i-out[N-i].i;
       X2r = (float)out[i].i+out[N-i].i;
       X2i = (float)out[N-i].r-out[i].r;

       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)float2int(d2_angle);
       noisiness[i] = ABS16(mod1);
       mod1 *= mod1;
       mod1 *= mod1;

       mod2 = d2_angle2 - (float)float2int(d2_angle2);
       noisiness[i] += ABS16(mod2);
       mod2 *= mod2;
       mod2 *= mod2;

       avg_mod = .25f*(d2A[i]+mod1+2*mod2);
       /* This introduces an extra delay of 2 frames in the detection. */
       tonality[i] = 1.f/(1.f+40.f*16.f*pi4*avg_mod)-.015f;
       /* No delay on this detection, but it's less reliable. */
       tonality2[i] = 1.f/(1.f+40.f*16.f*pi4*mod2)-.015f;

       A[i] = angle2;
       dA[i] = d_angle2;
       d2A[i] = mod2;
    }
    for (i=2;i<N2-1;i++)
    {
       float tt = MIN32(tonality2[i], MAX32(tonality2[i-1], tonality2[i+1]));
       tonality[i] = .9f*MAX32(tonality[i], tt-.1f);
    }
    frame_tonality = 0;
    max_frame_tonality = 0;
    /*tw_sum = 0;*/
    info->activity = 0;
    frame_noisiness = 0;
    frame_stationarity = 0;
    if (!tonal->count)
    {
       for (b=0;b<NB_TBANDS;b++)
       {
          tonal->lowE[b] = 1e10;
          tonal->highE[b] = -1e10;
       }
    }
    relativeE = 0;
    frame_loudness = 0;
    /* The energy of the very first band is special because of DC. */
    {
       float E = 0;
       float X1r, X2r;
       X1r = 2*(float)out[0].r;
       X2r = 2*(float)out[0].i;
       E = X1r*X1r + X2r*X2r;
       for (i=1;i<4;i++)
       {
          float binE = out[i].r*(float)out[i].r + out[N-i].r*(float)out[N-i].r
                     + out[i].i*(float)out[i].i + out[N-i].i*(float)out[N-i].i;
          E += binE;
       }
       E = SCALE_ENER(E);
       band_log2[0] = .5f*1.442695f*(float)log(E+1e-10f);
    }
    for (b=0;b<NB_TBANDS;b++)
    {
       float E=0, tE=0, nE=0;
       float L1, L2;
       float stationarity;
       for (i=tbands[b];i<tbands[b+1];i++)
       {
          float binE = out[i].r*(float)out[i].r + out[N-i].r*(float)out[N-i].r
                     + out[i].i*(float)out[i].i + out[N-i].i*(float)out[N-i].i;
          binE = SCALE_ENER(binE);
          E += binE;
          tE += binE*MAX32(0, tonality[i]);
          nE += binE*2.f*(.5f-noisiness[i]);
       }
#ifndef FIXED_POINT
       /* Check for extreme band energies that could cause NaNs later. */
       if (!(E<1e9f) || celt_isnan(E))
       {
          info->valid = 0;
          RESTORE_STACK;
          return;
       }
#endif

       tonal->E[tonal->E_count][b] = E;
       frame_noisiness += nE/(1e-15f+E);

       frame_loudness += (float)sqrt(E+1e-10f);
       logE[b] = (float)log(E+1e-10f);
       band_log2[b+1] = .5f*1.442695f*(float)log(E+1e-10f);
       tonal->logE[tonal->E_count][b] = logE[b];
       if (tonal->count==0)
          tonal->highE[b] = tonal->lowE[b] = logE[b];
       if (tonal->highE[b] > tonal->lowE[b] + 7.5)
       {
          if (tonal->highE[b] - logE[b] > logE[b] - tonal->lowE[b])
             tonal->highE[b] -= .01f;
          else
             tonal->lowE[b] += .01f;
       }
       if (logE[b] > tonal->highE[b])
       {
          tonal->highE[b] = logE[b];
          tonal->lowE[b] = MAX32(tonal->highE[b]-15, tonal->lowE[b]);
       } else if (logE[b] < tonal->lowE[b])
       {
          tonal->lowE[b] = logE[b];
          tonal->highE[b] = MIN32(tonal->lowE[b]+15, tonal->highE[b]);
       }
       relativeE += (logE[b]-tonal->lowE[b])/(1e-15f + (tonal->highE[b]-tonal->lowE[b]));

       L1=L2=0;
       for (i=0;i<NB_FRAMES;i++)
       {
          L1 += (float)sqrt(tonal->E[i][b]);
          L2 += tonal->E[i][b];
       }

       stationarity = MIN16(0.99f,L1/(float)sqrt(1e-15+NB_FRAMES*L2));
       stationarity *= stationarity;
       stationarity *= stationarity;
       frame_stationarity += stationarity;
       /*band_tonality[b] = tE/(1e-15+E)*/;
       band_tonality[b] = MAX16(tE/(1e-15f+E), stationarity*tonal->prev_band_tonality[b]);
#if 0
       if (b>=NB_TONAL_SKIP_BANDS)
       {
          frame_tonality += tweight[b]*band_tonality[b];
          tw_sum += tweight[b];
       }
#else
       frame_tonality += band_tonality[b];
       if (b>=NB_TBANDS-NB_TONAL_SKIP_BANDS)
          frame_tonality -= band_tonality[b-NB_TBANDS+NB_TONAL_SKIP_BANDS];
#endif
       max_frame_tonality = MAX16(max_frame_tonality, (1.f+.03f*(b-NB_TBANDS))*frame_tonality);
       slope += band_tonality[b]*(b-8);
       /*printf("%f %f ", band_tonality[b], stationarity);*/
       tonal->prev_band_tonality[b] = band_tonality[b];
    }

    leakage_from[0] = band_log2[0];
    leakage_to[0] = band_log2[0] - LEAKAGE_OFFSET;
    for (b=1;b<NB_TBANDS+1;b++)
    {
       float leak_slope = LEAKAGE_SLOPE*(tbands[b]-tbands[b-1])/4;
       leakage_from[b] = MIN16(leakage_from[b-1]+leak_slope, band_log2[b]);
       leakage_to[b] = MAX16(leakage_to[b-1]-leak_slope, band_log2[b]-LEAKAGE_OFFSET);
    }
    for (b=NB_TBANDS-2;b>=0;b--)
    {
       float leak_slope = LEAKAGE_SLOPE*(tbands[b+1]-tbands[b])/4;
       leakage_from[b] = MIN16(leakage_from[b+1]+leak_slope, leakage_from[b]);
       leakage_to[b] = MAX16(leakage_to[b+1]-leak_slope, leakage_to[b]);
    }
    celt_assert(NB_TBANDS+1 <= LEAK_BANDS);
    for (b=0;b<NB_TBANDS+1;b++)
    {
       /* leak_boost[] is made up of two terms. The first, based on leakage_to[],
          represents the boost needed to overcome the amount of analysis leakage
          cause in a weaker band b by louder neighbouring bands.
          The second, based on leakage_from[], applies to a loud band b for
          which the quantization noise causes synthesis leakage to the weaker
          neighbouring bands. */
       float boost = MAX16(0, leakage_to[b] - band_log2[b]) +
             MAX16(0, band_log2[b] - (leakage_from[b]+LEAKAGE_OFFSET));
       info->leak_boost[b] = IMIN(255, (int)floor(.5 + 64.f*boost));
    }
    for (;b<LEAK_BANDS;b++) info->leak_boost[b] = 0;

    for (i=0;i<NB_FRAMES;i++)
    {
       int j;
       float mindist = 1e15f;
       for (j=0;j<NB_FRAMES;j++)
       {
          int k;
          float dist=0;
          for (k=0;k<NB_TBANDS;k++)
          {
             float tmp;
             tmp = tonal->logE[i][k] - tonal->logE[j][k];
             dist += tmp*tmp;
          }
          if (j!=i)
             mindist = MIN32(mindist, dist);
       }
       spec_variability += mindist;
    }
    spec_variability = (float)sqrt(spec_variability/NB_FRAMES/NB_TBANDS);
    bandwidth_mask = 0;
    bandwidth = 0;
    maxE = 0;
    noise_floor = 5.7e-4f/(1<<(IMAX(0,lsb_depth-8)));
    noise_floor *= noise_floor;
    for (b=0;b<NB_TBANDS;b++)
    {
       float E=0;
       int band_start, band_end;
       /* Keep a margin of 300 Hz for aliasing */
       band_start = tbands[b];
       band_end = tbands[b+1];
       for (i=band_start;i<band_end;i++)
       {
          float binE = out[i].r*(float)out[i].r + out[N-i].r*(float)out[N-i].r
                     + out[i].i*(float)out[i].i + out[N-i].i*(float)out[N-i].i;
          E += binE;
       }
       E = SCALE_ENER(E);
       maxE = MAX32(maxE, E);
       tonal->meanE[b] = MAX32((1-alphaE2)*tonal->meanE[b], E);
       E = MAX32(E, tonal->meanE[b]);
       /* Use a simple follower with 13 dB/Bark slope for spreading function */
       bandwidth_mask = 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
          We use b+1 because the first CELT band isn't included in tbands[]
       */
       if (E>.1*bandwidth_mask && E*1e9f > maxE && E > noise_floor*(band_end-band_start))
          bandwidth = b+1;
    }
    /* Special case for the last two bands, for which we don't have spectrum but only
       the energy above 12 kHz. */
    if (tonal->Fs == 48000) {
       float ratio;
       float E = hp_ener*(1.f/(240*240));
       ratio = tonal->prev_bandwidth==20 ? 0.03f : 0.07f;
#ifdef FIXED_POINT
       /* silk_resampler_down2_hp() shifted right by an extra 8 bits. */
       E *= 256.f*(1.f/Q15ONE)*(1.f/Q15ONE);
#endif
       maxE = MAX32(maxE, E);
       tonal->meanE[b] = MAX32((1-alphaE2)*tonal->meanE[b], E);
       E = MAX32(E, tonal->meanE[b]);
       /* Use a simple follower with 13 dB/Bark slope for spreading function */
       bandwidth_mask = MAX32(.05f*bandwidth_mask, E);
       if (E>ratio*bandwidth_mask && E*1e9f > maxE && E > noise_floor*160)
          bandwidth = 20;
       /* This detector is unreliable, so if the bandwidth is close to SWB, assume it's FB. */
       if (bandwidth >= 17)
          bandwidth = 20;
    }
    if (tonal->count<=2)
       bandwidth = 20;
    frame_loudness = 20*(float)log10(frame_loudness);
    tonal->Etracker = MAX32(tonal->Etracker-.003f, 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 += dct_table[i*16+b]*logE[b];
       BFCC[i] = sum;
    }
    for (i=0;i<8;i++)
    {
       float sum=0;
       for (b=0;b<16;b++)
          sum += dct_table[i*16+b]*.5f*(tonal->highE[b]+tonal->lowE[b]);
       midE[i] = sum;
    }

    frame_stationarity /= NB_TBANDS;
    relativeE /= NB_TBANDS;
    if (tonal->count<10)
       relativeE = .5f;
    frame_noisiness /= NB_TBANDS;
#if 1
    info->activity = frame_noisiness + (1-frame_noisiness)*relativeE;
#else
    info->activity = .5*(1+frame_noisiness-frame_stationarity);
#endif
    frame_tonality = (max_frame_tonality/(NB_TBANDS-NB_TONAL_SKIP_BANDS));
    frame_tonality = 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)%NB_FRAMES;
    tonal->count = IMIN(tonal->count+1, ANALYSIS_COUNT_MAX);
    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<4;i++)
       features[i] = BFCC[i]-midE[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)sqrt(tonal->std[i]) - std_feature_bias[i];
    features[18] = spec_variability - 0.78f;
    features[20] = info->tonality - 0.154723f;
    features[21] = info->activity - 0.724643f;
    features[22] = frame_stationarity - 0.743717f;
    features[23] = info->tonality_slope + 0.069216f;
    features[24] = tonal->lowECount - 0.067930f;

    mlp_process(&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)pow(frame_probs[0], 10);*/
    /* Probability of active audio (as opposed to silence) */
    frame_probs[1] = .5f*frame_probs[1]+.5f;
    frame_probs[1] *= frame_probs[1];

    /* Probability of speech or music vs noise */
    info->activity_probability = frame_probs[1];

    /*printf("%f %f\n", 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;
       float p, q;

       /* More silence transitions for speech than for music. */
       tau = .001f*tonal->music_prob + .01f*(1-tonal->music_prob);
       p = MAX16(.05f,MIN16(.95f,frame_probs[1]));
       q = MAX16(.05f,MIN16(.95f,tonal->vad_prob));
       beta = .02f+.05f*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->vad_prob)*(1-tau) +    tonal->vad_prob *tau;
       p1 =    tonal->vad_prob *(1-tau) + (1-tonal->vad_prob)*tau;
       /* We apply the current probability with exponent beta to work around
          the fact that the probability estimates aren't independent. */
       p0 *= (float)pow(1-frame_probs[1], beta);
       p1 *= (float)pow(frame_probs[1], beta);
       /* Normalise the probabilities to get the Marokv probability of music. */
       tonal->vad_prob = p1/(p0+p1);
       info->vad_prob = tonal->vad_prob;
       /* Consider that silence has a 50-50 probability of being speech or music. */
       frame_probs[0] = tonal->vad_prob*frame_probs[0] + (1-tonal->vad_prob)*.5f;

       /* One transition every 3 minutes of active audio */
       tau = .0001f;
       /* Adapt beta based on how "unexpected" the new prob is */
       p = MAX16(.05f,MIN16(.95f,frame_probs[0]));
       q = MAX16(.05f,MIN16(.95f,tonal->music_prob));
       beta = .02f+.05f*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)pow(1-frame_probs[0], beta);
       p1 *= (float)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;

       /*printf("%f %f %f %f\n", frame_probs[0], frame_probs[1], tonal->music_prob, tonal->vad_prob);*/
       /* This chunk of code deals with delayed decision. */
       psum=1e-20f;
       /* Instantaneous probability of speech and music, with beta pre-applied. */
       speech0 = (float)pow(1-frame_probs[0], beta);
       music0  = (float)pow(frame_probs[0], beta);
       if (tonal->count==1)
       {
          if (tonal->application == OPUS_APPLICATION_VOIP)
             tonal->pmusic[0] = .1f;
          else
             tonal->pmusic[0] = .625f;
          tonal->pspeech[0] = 1-tonal->pmusic[0];
       }
       /* 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<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[DETECT_SIZE-1] = m0*tau*speech0;
       /* Probability that the latest frame is music, when all the previous ones were speech. */
       tonal->pmusic [DETECT_SIZE-1] = s0*tau*music0;

       /* Renormalise probabilities to 1 */
       for (i=0;i<DETECT_SIZE;i++)
          psum += tonal->pspeech[i] + tonal->pmusic[i];
       psum = 1.f/psum;
       for (i=0;i<DETECT_SIZE;i++)
       {
          tonal->pspeech[i] *= psum;
          tonal->pmusic [i] *= psum;
       }
       psum = tonal->pmusic[0];
       for (i=1;i<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.f/(++tonal->music_confidence_count);
             tonal->music_confidence_count = IMIN(tonal->music_confidence_count, 500);
             tonal->music_confidence += adapt*MAX16(-.2f,frame_probs[0]-tonal->music_confidence);
          }
          if (tonal->music_prob<.1)
          {
             float adapt;
             adapt = 1.f/(++tonal->speech_confidence_count);
             tonal->speech_confidence_count = IMIN(tonal->speech_confidence_count, 500);
             tonal->speech_confidence += adapt*MIN16(.2f,frame_probs[0]-tonal->speech_confidence);
          }
       }
    }
    tonal->last_music = tonal->music_prob>.5f;
#ifdef MLP_TRAINING
    for (i=0;i<25;i++)
       printf("%f ", features[i]);
    printf("\n");
#endif

    info->bandwidth = bandwidth;
    tonal->prev_bandwidth = bandwidth;
    /*printf("%d %d\n", info->bandwidth, info->opus_bandwidth);*/
    info->noisiness = frame_noisiness;
    info->valid = 1;
    RESTORE_STACK;
}