Index: third_party/opus/src/silk/float/noise_shape_analysis_FLP.c |
diff --git a/third_party/opus/src/silk/float/noise_shape_analysis_FLP.c b/third_party/opus/src/silk/float/noise_shape_analysis_FLP.c |
index 65f6ea587053819cdb141c04eb7dcf90e8ded754..cb3d8a50b7cb77095bfc2bf87359a5b71cfd3dc5 100644 |
--- a/third_party/opus/src/silk/float/noise_shape_analysis_FLP.c |
+++ b/third_party/opus/src/silk/float/noise_shape_analysis_FLP.c |
@@ -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; |
- |
- 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; |
- } |
+ BWExp = BANDWIDTH_EXPANSION / ( 1.0f + strength * strength ); |
+ |
+ /* 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 ); |
- |
- /* 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 ) ); |
+ silk_bwexpander_FLP( &psEncCtrl->AR[ k * MAX_SHAPE_LPC_ORDER ], psEnc->sCmn.shapingLPCOrder, BWExp ); |
- /* 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 ); |