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Issue #1890 - Update libopus

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This resolves #1890
This commit is contained in:
Moonchild 2022-05-04 17:03:37 +00:00 • committed by roytam1
commit a8b1099a1e
228 changed files with 10990 additions and 5670 deletions
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147
media/libopus/silk/float/noise_shape_analysis_FLP.c
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@ -55,25 +55,21 @@ static OPUS_INLINE silk_float warped_gain(
/* Convert warped filter coefficients to monic pseudo-warped coefficients and limit maximum */
/* amplitude of monic warped coefficients by using bandwidth expansion on the true coefficients */
static OPUS_INLINE void warped_true2monic_coefs(
silk_float *coefs_syn,
silk_float *coefs_ana,
silk_float *coefs,
silk_float lambda,
silk_float limit,
opus_int order
) {
opus_int i, iter, ind = 0;
silk_float tmp, maxabs, chirp, gain_syn, gain_ana;
silk_float tmp, maxabs, chirp, gain;
/* Convert to monic coefficients */
for( i = order - 1; i > 0; i-- ) {
coefs_syn[ i - 1 ] -= lambda * coefs_syn[ i ];
coefs_ana[ i - 1 ] -= lambda * coefs_ana[ i ];
coefs[ i - 1 ] -= lambda * coefs[ i ];
}
gain_syn = ( 1.0f - lambda * lambda ) / ( 1.0f + lambda * coefs_syn[ 0 ] );
gain_ana = ( 1.0f - lambda * lambda ) / ( 1.0f + lambda * coefs_ana[ 0 ] );
gain = ( 1.0f - lambda * lambda ) / ( 1.0f + lambda * coefs[ 0 ] );
for( i = 0; i < order; i++ ) {
coefs_syn[ i ] *= gain_syn;
coefs_ana[ i ] *= gain_ana;
coefs[ i ] *= gain;
}
/* Limit */
@ -81,7 +77,7 @@ static OPUS_INLINE void warped_true2monic_coefs(
/* Find maximum absolute value */
maxabs = -1.0f;
for( i = 0; i < order; i++ ) {
tmp = silk_max( silk_abs_float( coefs_syn[ i ] ), silk_abs_float( coefs_ana[ i ] ) );
tmp = silk_abs_float( coefs[ i ] );
if( tmp > maxabs ) {
maxabs = tmp;
ind = i;
@ -94,36 +90,59 @@ static OPUS_INLINE void warped_true2monic_coefs(
/* Convert back to true warped coefficients */
for( i = 1; i < order; i++ ) {
coefs_syn[ i - 1 ] += lambda * coefs_syn[ i ];
coefs_ana[ i - 1 ] += lambda * coefs_ana[ i ];
coefs[ i - 1 ] += lambda * coefs[ i ];
}
gain_syn = 1.0f / gain_syn;
gain_ana = 1.0f / gain_ana;
gain = 1.0f / gain;
for( i = 0; i < order; i++ ) {
coefs_syn[ i ] *= gain_syn;
coefs_ana[ i ] *= gain_ana;
coefs[ i ] *= gain;
}
/* Apply bandwidth expansion */
chirp = 0.99f - ( 0.8f + 0.1f * iter ) * ( maxabs - limit ) / ( maxabs * ( ind + 1 ) );
silk_bwexpander_FLP( coefs_syn, order, chirp );
silk_bwexpander_FLP( coefs_ana, order, chirp );
silk_bwexpander_FLP( coefs, order, chirp );
/* Convert to monic warped coefficients */
for( i = order - 1; i > 0; i-- ) {
coefs_syn[ i - 1 ] -= lambda * coefs_syn[ i ];
coefs_ana[ i - 1 ] -= lambda * coefs_ana[ i ];
coefs[ i - 1 ] -= lambda * coefs[ i ];
}
gain_syn = ( 1.0f - lambda * lambda ) / ( 1.0f + lambda * coefs_syn[ 0 ] );
gain_ana = ( 1.0f - lambda * lambda ) / ( 1.0f + lambda * coefs_ana[ 0 ] );
gain = ( 1.0f - lambda * lambda ) / ( 1.0f + lambda * coefs[ 0 ] );
for( i = 0; i < order; i++ ) {
coefs_syn[ i ] *= gain_syn;
coefs_ana[ i ] *= gain_ana;
coefs[ i ] *= gain;
}
}
silk_assert( 0 );
}
static OPUS_INLINE void limit_coefs(
silk_float *coefs,
silk_float limit,
opus_int order
) {
opus_int i, iter, ind = 0;
silk_float tmp, maxabs, chirp;
for( iter = 0; iter < 10; iter++ ) {
/* Find maximum absolute value */
maxabs = -1.0f;
for( i = 0; i < order; i++ ) {
tmp = silk_abs_float( coefs[ i ] );
if( tmp > maxabs ) {
maxabs = tmp;
ind = i;
}
}
if( maxabs <= limit ) {
/* Coefficients are within range - done */
return;
}
/* Apply bandwidth expansion */
chirp = 0.99f - ( 0.8f + 0.1f * iter ) * ( maxabs - limit ) / ( maxabs * ( ind + 1 ) );
silk_bwexpander_FLP( coefs, order, chirp );
}
silk_assert( 0 );
}
/* Compute noise shaping coefficients and initial gain values */
void silk_noise_shape_analysis_FLP(
silk_encoder_state_FLP *psEnc, /* I/O Encoder state FLP */
@ -133,12 +152,13 @@ void silk_noise_shape_analysis_FLP(
)
{
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;
opus_int k, nSamples, nSegs;
silk_float SNR_adj_dB, HarmShapeGain, Tilt;
silk_float nrg, log_energy, log_energy_prev, energy_variation;
silk_float BWExp, gain_mult, gain_add, strength, b, warping;
silk_float x_windowed[ SHAPE_LPC_WIN_MAX ];
silk_float auto_corr[ MAX_SHAPE_LPC_ORDER + 1 ];
silk_float rc[ MAX_SHAPE_LPC_ORDER + 1 ];
const silk_float *x_ptr, *pitch_res_ptr;
/* Point to start of first LPC analysis block */
@ -176,14 +196,14 @@ void silk_noise_shape_analysis_FLP(
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++ ) {
nSegs = silk_SMULBB( SUB_FRAME_LENGTH_MS, psEnc->sCmn.nb_subfr ) / 2;
for( k = 0; k < nSegs; k++ ) {
nrg = ( silk_float )nSamples + ( silk_float )silk_energy_FLP( pitch_res_ptr, nSamples );
log_energy = silk_log2( nrg );
if( k > 0 ) {
@ -192,17 +212,13 @@ void silk_noise_shape_analysis_FLP(
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 ) {
if( energy_variation > ENERGY_VARIATION_THRESHOLD_QNT_OFFSET * (nSegs-1) ) {
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 );
}
/*******************************/
@ -210,19 +226,10 @@ void silk_noise_shape_analysis_FLP(
/*******************************/
/* 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;
BWExp = BANDWIDTH_EXPANSION / ( 1.0f + strength * strength );
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;
}
/* 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;
/********************************************/
/* Compute noise shaping AR coefs and gains */
@ -252,37 +259,28 @@ void silk_noise_shape_analysis_FLP(
}
/* Add white noise, as a fraction of energy */
auto_corr[ 0 ] += auto_corr[ 0 ] * SHAPE_WHITE_NOISE_FRACTION;
auto_corr[ 0 ] += auto_corr[ 0 ] * SHAPE_WHITE_NOISE_FRACTION + 1.0f;
/* 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 );
nrg = silk_schur_FLP( rc, auto_corr, psEnc->sCmn.shapingLPCOrder );
silk_k2a_FLP( &psEncCtrl->AR[ k * MAX_SHAPE_LPC_ORDER ], rc, 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 );
psEncCtrl->Gains[ k ] *= warped_gain( &psEncCtrl->AR[ 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 );
silk_bwexpander_FLP( &psEncCtrl->AR[ k * MAX_SHAPE_LPC_ORDER ], psEnc->sCmn.shapingLPCOrder, BWExp );
/* 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 );
if( psEnc->sCmn.warping_Q16 > 0 ) {
/* Convert to monic warped prediction coefficients and limit absolute values */
warped_true2monic_coefs( &psEncCtrl->AR[ k * MAX_SHAPE_LPC_ORDER ], warping, 3.999f, psEnc->sCmn.shapingLPCOrder );
} else {
/* Limit absolute values */
limit_coefs( &psEncCtrl->AR[ k * MAX_SHAPE_LPC_ORDER ], 3.999f, psEnc->sCmn.shapingLPCOrder );
}
}
/*****************/
@ -296,11 +294,6 @@ void silk_noise_shape_analysis_FLP(
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 */
/************************************************/
@ -331,12 +324,6 @@ void silk_noise_shape_analysis_FLP(
/****************************/
/* 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;
@ -355,8 +342,6 @@ void silk_noise_shape_analysis_FLP(
/* 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 );