annotate src/opus-1.3/silk/float/noise_shape_analysis_FLP.c @ 83:ae30d91d2ffe

Replace these with versions built using an older toolset (so as to avoid ABI compatibilities when linking on Ubuntu 14.04 for packaging purposes)

/***********************************************************************
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THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE
ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE
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***********************************************************************/

#ifdef HAVE_CONFIG_H
#include "config.h"
#endif

#include "main_FLP.h"
#include "tuning_parameters.h"

/* Compute gain to make warped filter coefficients have a zero mean log frequency response on a   */
/* non-warped frequency scale. (So that it can be implemented with a minimum-phase monic filter.) */
/* Note: A monic filter is one with the first coefficient equal to 1.0. In Silk we omit the first */
/* coefficient in an array of coefficients, for monic filters.                                    */
static OPUS_INLINE silk_float warped_gain(
    const silk_float     *coefs,
    silk_float           lambda,
    opus_int             order
) {
    opus_int   i;
    silk_float gain;

    lambda = -lambda;
    gain = coefs[ order - 1 ];
    for( i = order - 2; i >= 0; i-- ) {
        gain = lambda * gain + coefs[ i ];
    }
    return (silk_float)( 1.0f / ( 1.0f - lambda * 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,
    silk_float           lambda,
    silk_float           limit,
    opus_int             order
) {
    opus_int   i, iter, ind = 0;
    silk_float tmp, maxabs, chirp, gain;

    /* Convert to monic coefficients */
    for( i = order - 1; i > 0; i-- ) {
        coefs[ i - 1 ] -= lambda * coefs[ i ];
    }
    gain = ( 1.0f - lambda * lambda ) / ( 1.0f + lambda * coefs[ 0 ] );
    for( i = 0; i < order; i++ ) {
        coefs[ i ] *= gain;
    }

    /* Limit */
    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;
        }

        /* Convert back to true warped coefficients */
        for( i = 1; i < order; i++ ) {
            coefs[ i - 1 ] += lambda * coefs[ i ];
        }
        gain = 1.0f / gain;
        for( i = 0; i < order; i++ ) {
            coefs[ i ] *= gain;
        }

        /* Apply bandwidth expansion */
        chirp = 0.99f - ( 0.8f + 0.1f * iter ) * ( maxabs - limit ) / ( maxabs * ( ind + 1 ) );
        silk_bwexpander_FLP( coefs, order, chirp );

        /* Convert to monic warped coefficients */
        for( i = order - 1; i > 0; i-- ) {
            coefs[ i - 1 ] -= lambda * coefs[ i ];
        }
        gain = ( 1.0f - lambda * lambda ) / ( 1.0f + lambda * coefs[ 0 ] );
        for( i = 0; i < order; i++ ) {
            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                           */
    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, 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 */
    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;
    } 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;
        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 ) {
                energy_variation += silk_abs_float( log_energy - log_energy_prev );
            }
            log_energy_prev = log_energy;
            pitch_res_ptr += nSamples;
        }

        /* Set quantization offset depending on sparseness measure */
        if( energy_variation > ENERGY_VARIATION_THRESHOLD_QNT_OFFSET * (nSegs-1) ) {
            psEnc->sCmn.indices.quantOffsetType = 0;
        } else {
            psEnc->sCmn.indices.quantOffsetType = 1;
        }
    }

    /*******************************/
    /* 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 */
    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 */
    /********************************************/
    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 + 1.0f;

        /* Convert correlations to prediction coefficients, and compute residual energy */
        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->AR[ k * MAX_SHAPE_LPC_ORDER ], warping, psEnc->sCmn.shapingLPCOrder );
        }

        /* Bandwidth expansion for synthesis filter shaping */
        silk_bwexpander_FLP( &psEncCtrl->AR[ k * MAX_SHAPE_LPC_ORDER ], psEnc->sCmn.shapingLPCOrder, BWExp );

        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 );
        }
    }

    /*****************/
    /* 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;
    }

    /************************************************/
    /* 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 */
    /****************************/
    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->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;
    }
}