| 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 );
|
|
|