/* of preceding samples */
void silk_residual_energy_FLP(
silk_float nrgs[MAX_NB_SUBFR], /* O Residual energy per subframe */
const silk_float x[], /* I Input signal */
silk_float a[2][MAX_LPC_ORDER], /* I AR coefs for each frame half */
const silk_float gains[], /* I Quantization gains */
const opus_int subfr_length, /* I Subframe length */
const opus_int nb_subfr, /* I number of subframes */
const opus_int LPC_order /* I LPC order */
) {
opus_int shift;
silk_float *LPC_res_ptr, LPC_res[(MAX_FRAME_LENGTH + MAX_NB_SUBFR * MAX_LPC_ORDER) / 2];
LPC_res_ptr = LPC_res + LPC_order;
shift = LPC_order + subfr_length;
/* Filter input to create the LPC residual for each frame half, and measure subframe energies */
silk_LPC_analysis_filter_FLP(LPC_res, a[0], x + 0 * shift, 2 * shift, LPC_order);
nrgs[0] = (silk_float)(
gains[0] * gains[0] * silk_energy_FLP(LPC_res_ptr + 0 * shift, subfr_length));
nrgs[1] = (silk_float)(
gains[1] * gains[1] * silk_energy_FLP(LPC_res_ptr + 1 * shift, subfr_length));
if (nb_subfr == MAX_NB_SUBFR) {
silk_LPC_analysis_filter_FLP(LPC_res, a[1], x + 2 * shift, 2 * shift, LPC_order);
nrgs[2] = (silk_float)(
gains[2] * gains[2] * silk_energy_FLP(LPC_res_ptr + 0 * shift, subfr_length));
nrgs[3] = (silk_float)(
gains[3] * gains[3] * silk_energy_FLP(LPC_res_ptr + 1 * shift, subfr_length));
}
}
/* Calculates correlation matrix X'*X */
void silk_corrMatrix_FLP(const silk_float * x, /* I x vector [ L+order-1 ] used to create X */
const int L, /* I Length of vectors */
const int Order, /* I Max lag for correlation */
silk_float * XX /* O X'*X correlation matrix [order x order] */
)
{
int j, lag;
double energy;
const silk_float *ptr1, *ptr2;
ptr1 = &x[Order - 1]; /* First sample of column 0 of X */
energy = silk_energy_FLP(ptr1, L); /* X[:,0]'*X[:,0] */
matrix_ptr(XX, 0, 0, Order) = (silk_float) energy;
for (j = 1; j < Order; j++) {
/* Calculate X[:,j]'*X[:,j] */
energy += ptr1[-j] * ptr1[-j] - ptr1[L - j] * ptr1[L - j];
matrix_ptr(XX, j, j, Order) = (silk_float) energy;
}
ptr2 = &x[Order - 2]; /* First sample of column 1 of X */
for (lag = 1; lag < Order; lag++) {
/* Calculate X[:,0]'*X[:,lag] */
energy = silk_inner_product_FLP(ptr1, ptr2, L);
matrix_ptr(XX, lag, 0, Order) = (silk_float) energy;
matrix_ptr(XX, 0, lag, Order) = (silk_float) energy;
/* Calculate X[:,j]'*X[:,j + lag] */
for (j = 1; j < (Order - lag); j++) {
energy +=
ptr1[-j] * ptr2[-j] - ptr1[L - j] * ptr2[L - j];
matrix_ptr(XX, lag + j, j, Order) = (silk_float) energy;
matrix_ptr(XX, j, lag + j, Order) = (silk_float) energy;
}
ptr2--; /* Next column of X */
}
}
/* Compute reflection coefficients from input signal */
silk_float silk_burg_modified_FLP( /* O returns residual energy */
silk_float A[], /* O prediction coefficients (length order) */
const silk_float x[], /* I input signal, length: nb_subfr*(D+L_sub) */
const silk_float minInvGain, /* I minimum inverse prediction gain */
const opus_int subfr_length, /* I input signal subframe length (incl. D preceding samples) */
const opus_int nb_subfr, /* I number of subframes stacked in x */
const opus_int D /* I order */
)
{
opus_int k, n, s, reached_max_gain;
double C0, invGain, num, nrg_f, nrg_b, rc, Atmp, tmp1, tmp2;
const silk_float *x_ptr;
double C_first_row[ SILK_MAX_ORDER_LPC ], C_last_row[ SILK_MAX_ORDER_LPC ];
double CAf[ SILK_MAX_ORDER_LPC + 1 ], CAb[ SILK_MAX_ORDER_LPC + 1 ];
double Af[ SILK_MAX_ORDER_LPC ];
silk_assert( subfr_length * nb_subfr <= MAX_FRAME_SIZE );
/* Compute autocorrelations, added over subframes */
C0 = silk_energy_FLP( x, nb_subfr * subfr_length );
silk_memset( C_first_row, 0, SILK_MAX_ORDER_LPC * sizeof( double ) );
for( s = 0; s < nb_subfr; s++ ) {
x_ptr = x + s * subfr_length;
for( n = 1; n < D + 1; n++ ) {
C_first_row[ n - 1 ] += silk_inner_product_FLP( x_ptr, x_ptr + n, subfr_length - n );
}
}
silk_memcpy( C_last_row, C_first_row, SILK_MAX_ORDER_LPC * sizeof( double ) );
/* Initialize */
CAb[ 0 ] = CAf[ 0 ] = C0 + FIND_LPC_COND_FAC * C0 + 1e-9f;
invGain = 1.0f;
reached_max_gain = 0;
for( n = 0; n < D; n++ ) {
/* Update first row of correlation matrix (without first element) */
/* Update last row of correlation matrix (without last element, stored in reversed order) */
/* Update C * Af */
/* Update C * flipud(Af) (stored in reversed order) */
for( s = 0; s < nb_subfr; s++ ) {
x_ptr = x + s * subfr_length;
tmp1 = x_ptr[ n ];
tmp2 = x_ptr[ subfr_length - n - 1 ];
for( k = 0; k < n; k++ ) {
C_first_row[ k ] -= x_ptr[ n ] * x_ptr[ n - k - 1 ];
C_last_row[ k ] -= x_ptr[ subfr_length - n - 1 ] * x_ptr[ subfr_length - n + k ];
Atmp = Af[ k ];
tmp1 += x_ptr[ n - k - 1 ] * Atmp;
tmp2 += x_ptr[ subfr_length - n + k ] * Atmp;
}
for( k = 0; k <= n; k++ ) {
CAf[ k ] -= tmp1 * x_ptr[ n - k ];
CAb[ k ] -= tmp2 * x_ptr[ subfr_length - n + k - 1 ];
}
}
tmp1 = C_first_row[ n ];
tmp2 = C_last_row[ n ];
for( k = 0; k < n; k++ ) {
Atmp = Af[ k ];
tmp1 += C_last_row[ n - k - 1 ] * Atmp;
tmp2 += C_first_row[ n - k - 1 ] * Atmp;
}
CAf[ n + 1 ] = tmp1;
CAb[ n + 1 ] = tmp2;
/* Calculate nominator and denominator for the next order reflection (parcor) coefficient */
num = CAb[ n + 1 ];
nrg_b = CAb[ 0 ];
nrg_f = CAf[ 0 ];
for( k = 0; k < n; k++ ) {
Atmp = Af[ k ];
num += CAb[ n - k ] * Atmp;
nrg_b += CAb[ k + 1 ] * Atmp;
nrg_f += CAf[ k + 1 ] * Atmp;
}
silk_assert( nrg_f > 0.0 );
silk_assert( nrg_b > 0.0 );
/* Calculate the next order reflection (parcor) coefficient */
rc = -2.0 * num / ( nrg_f + nrg_b );
silk_assert( rc > -1.0 && rc < 1.0 );
/* Update inverse prediction gain */
tmp1 = invGain * ( 1.0 - rc * rc );
if( tmp1 <= minInvGain ) {
/* Max prediction gain exceeded; set reflection coefficient such that max prediction gain is exactly hit */
rc = sqrt( 1.0 - minInvGain / invGain );
if( num > 0 ) {
/* Ensure adjusted reflection coefficients has the original sign */
rc = -rc;
}
invGain = minInvGain;
reached_max_gain = 1;
} else {
invGain = tmp1;
}
/* Update the AR coefficients */
for( k = 0; k < (n + 1) >> 1; k++ ) {
tmp1 = Af[ k ];
tmp2 = Af[ n - k - 1 ];
Af[ k ] = tmp1 + rc * tmp2;
Af[ n - k - 1 ] = tmp2 + rc * tmp1;
}
Af[ n ] = rc;
if( reached_max_gain ) {
/* Reached max prediction gain; set remaining coefficients to zero and exit loop */
for( k = n + 1; k < D; k++ ) {
Af[ k ] = 0.0;
}
break;
}
/* Update C * Af and C * Ab */
for( k = 0; k <= n + 1; k++ ) {
tmp1 = CAf[ k ];
CAf[ k ] += rc * CAb[ n - k + 1 ];
CAb[ n - k + 1 ] += rc * tmp1;
}
}
if( reached_max_gain ) {
/* Convert to silk_float */
for( k = 0; k < D; k++ ) {
A[ k ] = (silk_float)( -Af[ k ] );
}
/* Subtract energy of preceding samples from C0 */
for( s = 0; s < nb_subfr; s++ ) {
C0 -= silk_energy_FLP( x + s * subfr_length, D );
}
/* Approximate residual energy */
nrg_f = C0 * invGain;
} else {
/* Compute residual energy and store coefficients as silk_float */
nrg_f = CAf[ 0 ];
tmp1 = 1.0;
for( k = 0; k < D; k++ ) {
Atmp = Af[ k ];
nrg_f += CAf[ k + 1 ] * Atmp;
tmp1 += Atmp * Atmp;
A[ k ] = (silk_float)(-Atmp);
}
nrg_f -= FIND_LPC_COND_FAC * C0 * tmp1;
}
/* Return residual energy */
return (silk_float)nrg_f;
}
/* Compute noise shaping coefficients and initial gain values */
void silk_noise_shape_analysis_FLP(
silk_encoder_state_FLP *psEnc, /* I/O Encoder state FLP */
silk_encoder_control_FLP *psEncCtrl, /* I/O Encoder control FLP */
const silk_float *pitch_res, /* I LPC residual from pitch analysis */
const silk_float *x /* I Input signal [frame_length + la_shape] */
)
{
silk_shape_state_FLP *psShapeSt = &psEnc->sShape;
opus_int k, nSamples;
silk_float SNR_adj_dB, HarmBoost, HarmShapeGain, Tilt;
silk_float nrg, pre_nrg, log_energy, log_energy_prev, energy_variation;
silk_float delta, BWExp1, BWExp2, gain_mult, gain_add, strength, b, warping;
silk_float x_windowed[ SHAPE_LPC_WIN_MAX ];
silk_float auto_corr[ MAX_SHAPE_LPC_ORDER + 1 ];
const silk_float *x_ptr, *pitch_res_ptr;
/* Point to start of first LPC analysis block */
x_ptr = x - psEnc->sCmn.la_shape;
/****************/
/* GAIN CONTROL */
/****************/
SNR_adj_dB = psEnc->sCmn.SNR_dB_Q7 * ( 1 / 128.0f );
/* Input quality is the average of the quality in the lowest two VAD bands */
psEncCtrl->input_quality = 0.5f * ( psEnc->sCmn.input_quality_bands_Q15[ 0 ] + psEnc->sCmn.input_quality_bands_Q15[ 1 ] ) * ( 1.0f / 32768.0f );
/* Coding quality level, between 0.0 and 1.0 */
psEncCtrl->coding_quality = silk_sigmoid( 0.25f * ( SNR_adj_dB - 20.0f ) );
if( psEnc->sCmn.useCBR == 0 ) {
/* Reduce coding SNR during low speech activity */
b = 1.0f - psEnc->sCmn.speech_activity_Q8 * ( 1.0f / 256.0f );
SNR_adj_dB -= BG_SNR_DECR_dB * psEncCtrl->coding_quality * ( 0.5f + 0.5f * psEncCtrl->input_quality ) * b * b;
}
if( psEnc->sCmn.indices.signalType == TYPE_VOICED ) {
/* Reduce gains for periodic signals */
SNR_adj_dB += HARM_SNR_INCR_dB * psEnc->LTPCorr;
} else {
/* For unvoiced signals and low-quality input, adjust the quality slower than SNR_dB setting */
SNR_adj_dB += ( -0.4f * psEnc->sCmn.SNR_dB_Q7 * ( 1 / 128.0f ) + 6.0f ) * ( 1.0f - psEncCtrl->input_quality );
}
/*************************/
/* SPARSENESS PROCESSING */
/*************************/
/* Set quantizer offset */
if( psEnc->sCmn.indices.signalType == TYPE_VOICED ) {
/* Initially set to 0; may be overruled in process_gains(..) */
psEnc->sCmn.indices.quantOffsetType = 0;
psEncCtrl->sparseness = 0.0f;
} else {
/* Sparseness measure, based on relative fluctuations of energy per 2 milliseconds */
nSamples = 2 * psEnc->sCmn.fs_kHz;
energy_variation = 0.0f;
log_energy_prev = 0.0f;
pitch_res_ptr = pitch_res;
for( k = 0; k < silk_SMULBB( SUB_FRAME_LENGTH_MS, psEnc->sCmn.nb_subfr ) / 2; k++ ) {
nrg = ( silk_float )nSamples + ( silk_float )silk_energy_FLP( pitch_res_ptr, nSamples );
log_energy = silk_log2( nrg );
if( k > 0 ) {
energy_variation += silk_abs_float( log_energy - log_energy_prev );
}
log_energy_prev = log_energy;
pitch_res_ptr += nSamples;
}
psEncCtrl->sparseness = silk_sigmoid( 0.4f * ( energy_variation - 5.0f ) );
/* Set quantization offset depending on sparseness measure */
if( psEncCtrl->sparseness > SPARSENESS_THRESHOLD_QNT_OFFSET ) {
psEnc->sCmn.indices.quantOffsetType = 0;
} else {
psEnc->sCmn.indices.quantOffsetType = 1;
}
/* Increase coding SNR for sparse signals */
SNR_adj_dB += SPARSE_SNR_INCR_dB * ( psEncCtrl->sparseness - 0.5f );
}
/*******************************/
/* Control bandwidth expansion */
/*******************************/
/* More BWE for signals with high prediction gain */
strength = FIND_PITCH_WHITE_NOISE_FRACTION * psEncCtrl->predGain; /* between 0.0 and 1.0 */
BWExp1 = BWExp2 = BANDWIDTH_EXPANSION / ( 1.0f + strength * strength );
delta = LOW_RATE_BANDWIDTH_EXPANSION_DELTA * ( 1.0f - 0.75f * psEncCtrl->coding_quality );
BWExp1 -= delta;
BWExp2 += delta;
/* BWExp1 will be applied after BWExp2, so make it relative */
BWExp1 /= BWExp2;
if( psEnc->sCmn.warping_Q16 > 0 ) {
/* Slightly more warping in analysis will move quantization noise up in frequency, where it's better masked */
warping = (silk_float)psEnc->sCmn.warping_Q16 / 65536.0f + 0.01f * psEncCtrl->coding_quality;
} else {
warping = 0.0f;
}
/********************************************/
/* Compute noise shaping AR coefs and gains */
/********************************************/
for( k = 0; k < psEnc->sCmn.nb_subfr; k++ ) {
/* Apply window: sine slope followed by flat part followed by cosine slope */
opus_int shift, slope_part, flat_part;
flat_part = psEnc->sCmn.fs_kHz * 3;
slope_part = ( psEnc->sCmn.shapeWinLength - flat_part ) / 2;
silk_apply_sine_window_FLP( x_windowed, x_ptr, 1, slope_part );
shift = slope_part;
silk_memcpy( x_windowed + shift, x_ptr + shift, flat_part * sizeof(silk_float) );
shift += flat_part;
silk_apply_sine_window_FLP( x_windowed + shift, x_ptr + shift, 2, slope_part );
/* Update pointer: next LPC analysis block */
x_ptr += psEnc->sCmn.subfr_length;
if( psEnc->sCmn.warping_Q16 > 0 ) {
/* Calculate warped auto correlation */
silk_warped_autocorrelation_FLP( auto_corr, x_windowed, warping,
psEnc->sCmn.shapeWinLength, psEnc->sCmn.shapingLPCOrder );
} else {
/* Calculate regular auto correlation */
silk_autocorrelation_FLP( auto_corr, x_windowed, psEnc->sCmn.shapeWinLength, psEnc->sCmn.shapingLPCOrder + 1 );
}
/* Add white noise, as a fraction of energy */
auto_corr[ 0 ] += auto_corr[ 0 ] * SHAPE_WHITE_NOISE_FRACTION;
/* Convert correlations to prediction coefficients, and compute residual energy */
nrg = silk_levinsondurbin_FLP( &psEncCtrl->AR2[ k * MAX_SHAPE_LPC_ORDER ], auto_corr, psEnc->sCmn.shapingLPCOrder );
psEncCtrl->Gains[ k ] = ( silk_float )sqrt( nrg );
if( psEnc->sCmn.warping_Q16 > 0 ) {
/* Adjust gain for warping */
psEncCtrl->Gains[ k ] *= warped_gain( &psEncCtrl->AR2[ k * MAX_SHAPE_LPC_ORDER ], warping, psEnc->sCmn.shapingLPCOrder );
}
/* Bandwidth expansion for synthesis filter shaping */
silk_bwexpander_FLP( &psEncCtrl->AR2[ k * MAX_SHAPE_LPC_ORDER ], psEnc->sCmn.shapingLPCOrder, BWExp2 );
/* Compute noise shaping filter coefficients */
silk_memcpy(
&psEncCtrl->AR1[ k * MAX_SHAPE_LPC_ORDER ],
&psEncCtrl->AR2[ k * MAX_SHAPE_LPC_ORDER ],
psEnc->sCmn.shapingLPCOrder * sizeof( silk_float ) );
/* Bandwidth expansion for analysis filter shaping */
silk_bwexpander_FLP( &psEncCtrl->AR1[ k * MAX_SHAPE_LPC_ORDER ], psEnc->sCmn.shapingLPCOrder, BWExp1 );
/* Ratio of prediction gains, in energy domain */
pre_nrg = silk_LPC_inverse_pred_gain_FLP( &psEncCtrl->AR2[ k * MAX_SHAPE_LPC_ORDER ], psEnc->sCmn.shapingLPCOrder );
nrg = silk_LPC_inverse_pred_gain_FLP( &psEncCtrl->AR1[ k * MAX_SHAPE_LPC_ORDER ], psEnc->sCmn.shapingLPCOrder );
psEncCtrl->GainsPre[ k ] = 1.0f - 0.7f * ( 1.0f - pre_nrg / nrg );
/* Convert to monic warped prediction coefficients and limit absolute values */
warped_true2monic_coefs( &psEncCtrl->AR2[ k * MAX_SHAPE_LPC_ORDER ], &psEncCtrl->AR1[ k * MAX_SHAPE_LPC_ORDER ],
warping, 3.999f, psEnc->sCmn.shapingLPCOrder );
}
/*****************/
/* Gain tweaking */
/*****************/
/* Increase gains during low speech activity */
gain_mult = (silk_float)pow( 2.0f, -0.16f * SNR_adj_dB );
gain_add = (silk_float)pow( 2.0f, 0.16f * MIN_QGAIN_DB );
for( k = 0; k < psEnc->sCmn.nb_subfr; k++ ) {
psEncCtrl->Gains[ k ] *= gain_mult;
psEncCtrl->Gains[ k ] += gain_add;
}
gain_mult = 1.0f + INPUT_TILT + psEncCtrl->coding_quality * HIGH_RATE_INPUT_TILT;
for( k = 0; k < psEnc->sCmn.nb_subfr; k++ ) {
psEncCtrl->GainsPre[ k ] *= gain_mult;
}
/************************************************/
/* Control low-frequency shaping and noise tilt */
/************************************************/
/* Less low frequency shaping for noisy inputs */
strength = LOW_FREQ_SHAPING * ( 1.0f + LOW_QUALITY_LOW_FREQ_SHAPING_DECR * ( psEnc->sCmn.input_quality_bands_Q15[ 0 ] * ( 1.0f / 32768.0f ) - 1.0f ) );
strength *= psEnc->sCmn.speech_activity_Q8 * ( 1.0f / 256.0f );
if( psEnc->sCmn.indices.signalType == TYPE_VOICED ) {
/* Reduce low frequencies quantization noise for periodic signals, depending on pitch lag */
/*f = 400; freqz([1, -0.98 + 2e-4 * f], [1, -0.97 + 7e-4 * f], 2^12, Fs); axis([0, 1000, -10, 1])*/
for( k = 0; k < psEnc->sCmn.nb_subfr; k++ ) {
b = 0.2f / psEnc->sCmn.fs_kHz + 3.0f / psEncCtrl->pitchL[ k ];
psEncCtrl->LF_MA_shp[ k ] = -1.0f + b;
psEncCtrl->LF_AR_shp[ k ] = 1.0f - b - b * strength;
}
Tilt = - HP_NOISE_COEF -
(1 - HP_NOISE_COEF) * HARM_HP_NOISE_COEF * psEnc->sCmn.speech_activity_Q8 * ( 1.0f / 256.0f );
} else {
b = 1.3f / psEnc->sCmn.fs_kHz;
psEncCtrl->LF_MA_shp[ 0 ] = -1.0f + b;
psEncCtrl->LF_AR_shp[ 0 ] = 1.0f - b - b * strength * 0.6f;
for( k = 1; k < psEnc->sCmn.nb_subfr; k++ ) {
psEncCtrl->LF_MA_shp[ k ] = psEncCtrl->LF_MA_shp[ 0 ];
psEncCtrl->LF_AR_shp[ k ] = psEncCtrl->LF_AR_shp[ 0 ];
}
Tilt = -HP_NOISE_COEF;
}
/****************************/
/* HARMONIC SHAPING CONTROL */
/****************************/
/* Control boosting of harmonic frequencies */
HarmBoost = LOW_RATE_HARMONIC_BOOST * ( 1.0f - psEncCtrl->coding_quality ) * psEnc->LTPCorr;
/* More harmonic boost for noisy input signals */
HarmBoost += LOW_INPUT_QUALITY_HARMONIC_BOOST * ( 1.0f - psEncCtrl->input_quality );
if( USE_HARM_SHAPING && psEnc->sCmn.indices.signalType == TYPE_VOICED ) {
/* Harmonic noise shaping */
HarmShapeGain = HARMONIC_SHAPING;
/* More harmonic noise shaping for high bitrates or noisy input */
HarmShapeGain += HIGH_RATE_OR_LOW_QUALITY_HARMONIC_SHAPING *
( 1.0f - ( 1.0f - psEncCtrl->coding_quality ) * psEncCtrl->input_quality );
/* Less harmonic noise shaping for less periodic signals */
HarmShapeGain *= ( silk_float )sqrt( psEnc->LTPCorr );
} else {
HarmShapeGain = 0.0f;
}
/*************************/
/* Smooth over subframes */
/*************************/
for( k = 0; k < psEnc->sCmn.nb_subfr; k++ ) {
psShapeSt->HarmBoost_smth += SUBFR_SMTH_COEF * ( HarmBoost - psShapeSt->HarmBoost_smth );
psEncCtrl->HarmBoost[ k ] = psShapeSt->HarmBoost_smth;
psShapeSt->HarmShapeGain_smth += SUBFR_SMTH_COEF * ( HarmShapeGain - psShapeSt->HarmShapeGain_smth );
psEncCtrl->HarmShapeGain[ k ] = psShapeSt->HarmShapeGain_smth;
psShapeSt->Tilt_smth += SUBFR_SMTH_COEF * ( Tilt - psShapeSt->Tilt_smth );
psEncCtrl->Tilt[ k ] = psShapeSt->Tilt_smth;
}
}
void silk_find_LTP_FLP(
silk_float b[ MAX_NB_SUBFR * LTP_ORDER ], /* O LTP coefs */
silk_float WLTP[ MAX_NB_SUBFR * LTP_ORDER * LTP_ORDER ], /* O Weight for LTP quantization */
silk_float *LTPredCodGain, /* O LTP coding gain */
const silk_float r_lpc[], /* I LPC residual */
const opus_int lag[ MAX_NB_SUBFR ], /* I LTP lags */
const silk_float Wght[ MAX_NB_SUBFR ], /* I Weights */
const opus_int subfr_length, /* I Subframe length */
const opus_int nb_subfr, /* I number of subframes */
const opus_int mem_offset /* I Number of samples in LTP memory */
)
{
opus_int i, k;
silk_float *b_ptr, temp, *WLTP_ptr;
silk_float LPC_res_nrg, LPC_LTP_res_nrg;
silk_float d[ MAX_NB_SUBFR ], m, g, delta_b[ LTP_ORDER ];
silk_float w[ MAX_NB_SUBFR ], nrg[ MAX_NB_SUBFR ], regu;
silk_float Rr[ LTP_ORDER ], rr[ MAX_NB_SUBFR ];
const silk_float *r_ptr, *lag_ptr;
b_ptr = b;
WLTP_ptr = WLTP;
r_ptr = &r_lpc[ mem_offset ];
for( k = 0; k < nb_subfr; k++ ) {
lag_ptr = r_ptr - ( lag[ k ] + LTP_ORDER / 2 );
silk_corrMatrix_FLP( lag_ptr, subfr_length, LTP_ORDER, WLTP_ptr );
silk_corrVector_FLP( lag_ptr, r_ptr, subfr_length, LTP_ORDER, Rr );
rr[ k ] = ( silk_float )silk_energy_FLP( r_ptr, subfr_length );
regu = 1.0f + rr[ k ] +
matrix_ptr( WLTP_ptr, 0, 0, LTP_ORDER ) +
matrix_ptr( WLTP_ptr, LTP_ORDER-1, LTP_ORDER-1, LTP_ORDER );
regu *= LTP_DAMPING / 3;
silk_regularize_correlations_FLP( WLTP_ptr, &rr[ k ], regu, LTP_ORDER );
silk_solve_LDL_FLP( WLTP_ptr, LTP_ORDER, Rr, b_ptr );
/* Calculate residual energy */
nrg[ k ] = silk_residual_energy_covar_FLP( b_ptr, WLTP_ptr, Rr, rr[ k ], LTP_ORDER );
temp = Wght[ k ] / ( nrg[ k ] * Wght[ k ] + 0.01f * subfr_length );
silk_scale_vector_FLP( WLTP_ptr, temp, LTP_ORDER * LTP_ORDER );
w[ k ] = matrix_ptr( WLTP_ptr, LTP_ORDER / 2, LTP_ORDER / 2, LTP_ORDER );
r_ptr += subfr_length;
b_ptr += LTP_ORDER;
WLTP_ptr += LTP_ORDER * LTP_ORDER;
}
/* Compute LTP coding gain */
if( LTPredCodGain != NULL ) {
LPC_LTP_res_nrg = 1e-6f;
LPC_res_nrg = 0.0f;
for( k = 0; k < nb_subfr; k++ ) {
LPC_res_nrg += rr[ k ] * Wght[ k ];
LPC_LTP_res_nrg += nrg[ k ] * Wght[ k ];
}
silk_assert( LPC_LTP_res_nrg > 0 );
*LTPredCodGain = 3.0f * silk_log2( LPC_res_nrg / LPC_LTP_res_nrg );
}
/* Smoothing */
/* d = sum( B, 1 ); */
b_ptr = b;
for( k = 0; k < nb_subfr; k++ ) {
d[ k ] = 0;
for( i = 0; i < LTP_ORDER; i++ ) {
d[ k ] += b_ptr[ i ];
}
b_ptr += LTP_ORDER;
}
/* m = ( w * d' ) / ( sum( w ) + 1e-3 ); */
temp = 1e-3f;
for( k = 0; k < nb_subfr; k++ ) {
temp += w[ k ];
}
m = 0;
for( k = 0; k < nb_subfr; k++ ) {
m += d[ k ] * w[ k ];
}
m = m / temp;
b_ptr = b;
for( k = 0; k < nb_subfr; k++ ) {
g = LTP_SMOOTHING / ( LTP_SMOOTHING + w[ k ] ) * ( m - d[ k ] );
temp = 0;
for( i = 0; i < LTP_ORDER; i++ ) {
delta_b[ i ] = silk_max_float( b_ptr[ i ], 0.1f );
temp += delta_b[ i ];
}
temp = g / temp;
for( i = 0; i < LTP_ORDER; i++ ) {
b_ptr[ i ] = b_ptr[ i ] + delta_b[ i ] * temp;
}
b_ptr += LTP_ORDER;
}
}
/* LPC analysis */
void silk_find_LPC_FLP(
silk_encoder_state *psEncC, /* I/O Encoder state */
opus_int16 NLSF_Q15[], /* O NLSFs */
const silk_float x[], /* I Input signal */
const silk_float minInvGain /* I Inverse of max prediction gain */
)
{
opus_int k, subfr_length;
silk_float a[ MAX_LPC_ORDER ];
/* Used only for NLSF interpolation */
silk_float res_nrg, res_nrg_2nd, res_nrg_interp;
opus_int16 NLSF0_Q15[ MAX_LPC_ORDER ];
silk_float a_tmp[ MAX_LPC_ORDER ];
silk_float LPC_res[ MAX_FRAME_LENGTH + MAX_NB_SUBFR * MAX_LPC_ORDER ];
subfr_length = psEncC->subfr_length + psEncC->predictLPCOrder;
/* Default: No interpolation */
psEncC->indices.NLSFInterpCoef_Q2 = 4;
/* Burg AR analysis for the full frame */
res_nrg = silk_burg_modified_FLP( a, x, minInvGain, subfr_length, psEncC->nb_subfr, psEncC->predictLPCOrder );
if( psEncC->useInterpolatedNLSFs && !psEncC->first_frame_after_reset && psEncC->nb_subfr == MAX_NB_SUBFR ) {
/* Optimal solution for last 10 ms; subtract residual energy here, as that's easier than */
/* adding it to the residual energy of the first 10 ms in each iteration of the search below */
res_nrg -= silk_burg_modified_FLP( a_tmp, x + ( MAX_NB_SUBFR / 2 ) * subfr_length, minInvGain, subfr_length, MAX_NB_SUBFR / 2, psEncC->predictLPCOrder );
/* Convert to NLSFs */
silk_A2NLSF_FLP( NLSF_Q15, a_tmp, psEncC->predictLPCOrder );
/* Search over interpolation indices to find the one with lowest residual energy */
res_nrg_2nd = silk_float_MAX;
for( k = 3; k >= 0; k-- ) {
/* Interpolate NLSFs for first half */
silk_interpolate( NLSF0_Q15, psEncC->prev_NLSFq_Q15, NLSF_Q15, k, psEncC->predictLPCOrder );
/* Convert to LPC for residual energy evaluation */
silk_NLSF2A_FLP( a_tmp, NLSF0_Q15, psEncC->predictLPCOrder );
/* Calculate residual energy with LSF interpolation */
silk_LPC_analysis_filter_FLP( LPC_res, a_tmp, x, 2 * subfr_length, psEncC->predictLPCOrder );
res_nrg_interp = (silk_float)(
silk_energy_FLP( LPC_res + psEncC->predictLPCOrder, subfr_length - psEncC->predictLPCOrder ) +
silk_energy_FLP( LPC_res + psEncC->predictLPCOrder + subfr_length, subfr_length - psEncC->predictLPCOrder ) );
/* Determine whether current interpolated NLSFs are best so far */
if( res_nrg_interp < res_nrg ) {
/* Interpolation has lower residual energy */
res_nrg = res_nrg_interp;
psEncC->indices.NLSFInterpCoef_Q2 = (opus_int8)k;
} else if( res_nrg_interp > res_nrg_2nd ) {
/* No reason to continue iterating - residual energies will continue to climb */
break;
}
res_nrg_2nd = res_nrg_interp;
}
}
if( psEncC->indices.NLSFInterpCoef_Q2 == 4 ) {
/* NLSF interpolation is currently inactive, calculate NLSFs from full frame AR coefficients */
silk_A2NLSF_FLP( NLSF_Q15, a, psEncC->predictLPCOrder );
}
silk_assert( psEncC->indices.NLSFInterpCoef_Q2 == 4 ||
( psEncC->useInterpolatedNLSFs && !psEncC->first_frame_after_reset && psEncC->nb_subfr == MAX_NB_SUBFR ) );
}
/* Compute reflection coefficients from input signal */
silk_float silk_burg_modified_FLP( /* O returns residual energy */
silk_float A[], /* O prediction coefficients (length order) */
const silk_float x[], /* I input signal, length: nb_subfr*(D+L_sub) */
const opus_int subfr_length, /* I input signal subframe length (incl. D preceeding samples) */
const opus_int nb_subfr, /* I number of subframes stacked in x */
const silk_float WhiteNoiseFrac, /* I fraction added to zero-lag autocorrelation */
const opus_int D /* I order */
)
{
opus_int k, n, s;
double C0, num, nrg_f, nrg_b, rc, Atmp, tmp1, tmp2;
const silk_float *x_ptr;
double C_first_row[ SILK_MAX_ORDER_LPC ], C_last_row[ SILK_MAX_ORDER_LPC ];
double CAf[ SILK_MAX_ORDER_LPC + 1 ], CAb[ SILK_MAX_ORDER_LPC + 1 ];
double Af[ SILK_MAX_ORDER_LPC ];
silk_assert( subfr_length * nb_subfr <= MAX_FRAME_SIZE );
silk_assert( nb_subfr <= MAX_NB_SUBFR );
/* Compute autocorrelations, added over subframes */
C0 = silk_energy_FLP( x, nb_subfr * subfr_length );
silk_memset( C_first_row, 0, SILK_MAX_ORDER_LPC * sizeof( double ) );
for( s = 0; s < nb_subfr; s++ ) {
x_ptr = x + s * subfr_length;
for( n = 1; n < D + 1; n++ ) {
C_first_row[ n - 1 ] += silk_inner_product_FLP( x_ptr, x_ptr + n, subfr_length - n );
}
}
silk_memcpy( C_last_row, C_first_row, SILK_MAX_ORDER_LPC * sizeof( double ) );
/* Initialize */
CAb[ 0 ] = CAf[ 0 ] = C0 + WhiteNoiseFrac * C0 + 1e-9f;
for( n = 0; n < D; n++ ) {
/* Update first row of correlation matrix (without first element) */
/* Update last row of correlation matrix (without last element, stored in reversed order) */
/* Update C * Af */
/* Update C * flipud(Af) (stored in reversed order) */
for( s = 0; s < nb_subfr; s++ ) {
x_ptr = x + s * subfr_length;
tmp1 = x_ptr[ n ];
tmp2 = x_ptr[ subfr_length - n - 1 ];
for( k = 0; k < n; k++ ) {
C_first_row[ k ] -= x_ptr[ n ] * x_ptr[ n - k - 1 ];
C_last_row[ k ] -= x_ptr[ subfr_length - n - 1 ] * x_ptr[ subfr_length - n + k ];
Atmp = Af[ k ];
tmp1 += x_ptr[ n - k - 1 ] * Atmp;
tmp2 += x_ptr[ subfr_length - n + k ] * Atmp;
}
for( k = 0; k <= n; k++ ) {
CAf[ k ] -= tmp1 * x_ptr[ n - k ];
CAb[ k ] -= tmp2 * x_ptr[ subfr_length - n + k - 1 ];
}
}
tmp1 = C_first_row[ n ];
tmp2 = C_last_row[ n ];
for( k = 0; k < n; k++ ) {
Atmp = Af[ k ];
tmp1 += C_last_row[ n - k - 1 ] * Atmp;
tmp2 += C_first_row[ n - k - 1 ] * Atmp;
}
CAf[ n + 1 ] = tmp1;
CAb[ n + 1 ] = tmp2;
/* Calculate nominator and denominator for the next order reflection (parcor) coefficient */
num = CAb[ n + 1 ];
nrg_b = CAb[ 0 ];
nrg_f = CAf[ 0 ];
for( k = 0; k < n; k++ ) {
Atmp = Af[ k ];
num += CAb[ n - k ] * Atmp;
nrg_b += CAb[ k + 1 ] * Atmp;
nrg_f += CAf[ k + 1 ] * Atmp;
}
silk_assert( nrg_f > 0.0 );
silk_assert( nrg_b > 0.0 );
/* Calculate the next order reflection (parcor) coefficient */
rc = -2.0 * num / ( nrg_f + nrg_b );
silk_assert( rc > -1.0 && rc < 1.0 );
/* Update the AR coefficients */
for( k = 0; k < (n + 1) >> 1; k++ ) {
tmp1 = Af[ k ];
tmp2 = Af[ n - k - 1 ];
Af[ k ] = tmp1 + rc * tmp2;
Af[ n - k - 1 ] = tmp2 + rc * tmp1;
}
Af[ n ] = rc;
/* Update C * Af and C * Ab */
for( k = 0; k <= n + 1; k++ ) {
tmp1 = CAf[ k ];
CAf[ k ] += rc * CAb[ n - k + 1 ];
CAb[ n - k + 1 ] += rc * tmp1;
}
}
/* Return residual energy */
nrg_f = CAf[ 0 ];
tmp1 = 1.0;
for( k = 0; k < D; k++ ) {
Atmp = Af[ k ];
nrg_f += CAf[ k + 1 ] * Atmp;
tmp1 += Atmp * Atmp;
A[ k ] = (silk_float)(-Atmp);
}
nrg_f -= WhiteNoiseFrac * C0 * tmp1;
return (silk_float)nrg_f;
}