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https://github.com/UberGames/ioef.git
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178 lines
7.7 KiB
C
178 lines
7.7 KiB
C
/***********************************************************************
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Copyright (c) 2006-2011, Skype Limited. All rights reserved.
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Redistribution and use in source and binary forms, with or without
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modification, are permitted provided that the following conditions
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are met:
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- Redistributions of source code must retain the above copyright notice,
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this list of conditions and the following disclaimer.
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- Redistributions in binary form must reproduce the above copyright
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notice, this list of conditions and the following disclaimer in the
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documentation and/or other materials provided with the distribution.
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- Neither the name of Internet Society, IETF or IETF Trust, nor the
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names of specific contributors, may be used to endorse or promote
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products derived from this software without specific prior written
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permission.
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THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
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AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
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IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE
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ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE
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LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR
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CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF
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SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS
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INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN
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CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)
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ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
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POSSIBILITY OF SUCH DAMAGE.
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***********************************************************************/
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#ifdef HAVE_CONFIG_H
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#include "config.h"
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#endif
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/* conversion between prediction filter coefficients and LSFs */
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/* order should be even */
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/* a piecewise linear approximation maps LSF <-> cos(LSF) */
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/* therefore the result is not accurate LSFs, but the two */
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/* functions are accurate inverses of each other */
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#include "SigProc_FIX.h"
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#include "tables.h"
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#define QA 16
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/* helper function for NLSF2A(..) */
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static OPUS_INLINE void silk_NLSF2A_find_poly(
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opus_int32 *out, /* O intermediate polynomial, QA [dd+1] */
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const opus_int32 *cLSF, /* I vector of interleaved 2*cos(LSFs), QA [d] */
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opus_int dd /* I polynomial order (= 1/2 * filter order) */
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)
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{
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opus_int k, n;
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opus_int32 ftmp;
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out[0] = silk_LSHIFT( 1, QA );
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out[1] = -cLSF[0];
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for( k = 1; k < dd; k++ ) {
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ftmp = cLSF[2*k]; /* QA*/
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out[k+1] = silk_LSHIFT( out[k-1], 1 ) - (opus_int32)silk_RSHIFT_ROUND64( silk_SMULL( ftmp, out[k] ), QA );
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for( n = k; n > 1; n-- ) {
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out[n] += out[n-2] - (opus_int32)silk_RSHIFT_ROUND64( silk_SMULL( ftmp, out[n-1] ), QA );
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}
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out[1] -= ftmp;
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}
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}
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/* compute whitening filter coefficients from normalized line spectral frequencies */
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void silk_NLSF2A(
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opus_int16 *a_Q12, /* O monic whitening filter coefficients in Q12, [ d ] */
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const opus_int16 *NLSF, /* I normalized line spectral frequencies in Q15, [ d ] */
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const opus_int d /* I filter order (should be even) */
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)
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{
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/* This ordering was found to maximize quality. It improves numerical accuracy of
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silk_NLSF2A_find_poly() compared to "standard" ordering. */
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static const unsigned char ordering16[16] = {
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0, 15, 8, 7, 4, 11, 12, 3, 2, 13, 10, 5, 6, 9, 14, 1
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};
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static const unsigned char ordering10[10] = {
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0, 9, 6, 3, 4, 5, 8, 1, 2, 7
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};
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const unsigned char *ordering;
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opus_int k, i, dd;
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opus_int32 cos_LSF_QA[ SILK_MAX_ORDER_LPC ];
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opus_int32 P[ SILK_MAX_ORDER_LPC / 2 + 1 ], Q[ SILK_MAX_ORDER_LPC / 2 + 1 ];
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opus_int32 Ptmp, Qtmp, f_int, f_frac, cos_val, delta;
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opus_int32 a32_QA1[ SILK_MAX_ORDER_LPC ];
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opus_int32 maxabs, absval, idx=0, sc_Q16;
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silk_assert( LSF_COS_TAB_SZ_FIX == 128 );
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silk_assert( d==10||d==16 );
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/* convert LSFs to 2*cos(LSF), using piecewise linear curve from table */
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ordering = d == 16 ? ordering16 : ordering10;
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for( k = 0; k < d; k++ ) {
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silk_assert(NLSF[k] >= 0 );
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/* f_int on a scale 0-127 (rounded down) */
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f_int = silk_RSHIFT( NLSF[k], 15 - 7 );
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/* f_frac, range: 0..255 */
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f_frac = NLSF[k] - silk_LSHIFT( f_int, 15 - 7 );
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silk_assert(f_int >= 0);
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silk_assert(f_int < LSF_COS_TAB_SZ_FIX );
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/* Read start and end value from table */
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cos_val = silk_LSFCosTab_FIX_Q12[ f_int ]; /* Q12 */
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delta = silk_LSFCosTab_FIX_Q12[ f_int + 1 ] - cos_val; /* Q12, with a range of 0..200 */
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/* Linear interpolation */
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cos_LSF_QA[ordering[k]] = silk_RSHIFT_ROUND( silk_LSHIFT( cos_val, 8 ) + silk_MUL( delta, f_frac ), 20 - QA ); /* QA */
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}
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dd = silk_RSHIFT( d, 1 );
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/* generate even and odd polynomials using convolution */
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silk_NLSF2A_find_poly( P, &cos_LSF_QA[ 0 ], dd );
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silk_NLSF2A_find_poly( Q, &cos_LSF_QA[ 1 ], dd );
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/* convert even and odd polynomials to opus_int32 Q12 filter coefs */
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for( k = 0; k < dd; k++ ) {
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Ptmp = P[ k+1 ] + P[ k ];
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Qtmp = Q[ k+1 ] - Q[ k ];
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/* the Ptmp and Qtmp values at this stage need to fit in int32 */
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a32_QA1[ k ] = -Qtmp - Ptmp; /* QA+1 */
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a32_QA1[ d-k-1 ] = Qtmp - Ptmp; /* QA+1 */
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}
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/* Limit the maximum absolute value of the prediction coefficients, so that they'll fit in int16 */
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for( i = 0; i < 10; i++ ) {
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/* Find maximum absolute value and its index */
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maxabs = 0;
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for( k = 0; k < d; k++ ) {
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absval = silk_abs( a32_QA1[k] );
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if( absval > maxabs ) {
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maxabs = absval;
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idx = k;
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}
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}
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maxabs = silk_RSHIFT_ROUND( maxabs, QA + 1 - 12 ); /* QA+1 -> Q12 */
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if( maxabs > silk_int16_MAX ) {
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/* Reduce magnitude of prediction coefficients */
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maxabs = silk_min( maxabs, 163838 ); /* ( silk_int32_MAX >> 14 ) + silk_int16_MAX = 163838 */
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sc_Q16 = SILK_FIX_CONST( 0.999, 16 ) - silk_DIV32( silk_LSHIFT( maxabs - silk_int16_MAX, 14 ),
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silk_RSHIFT32( silk_MUL( maxabs, idx + 1), 2 ) );
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silk_bwexpander_32( a32_QA1, d, sc_Q16 );
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} else {
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break;
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}
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}
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if( i == 10 ) {
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/* Reached the last iteration, clip the coefficients */
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for( k = 0; k < d; k++ ) {
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a_Q12[ k ] = (opus_int16)silk_SAT16( silk_RSHIFT_ROUND( a32_QA1[ k ], QA + 1 - 12 ) ); /* QA+1 -> Q12 */
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a32_QA1[ k ] = silk_LSHIFT( (opus_int32)a_Q12[ k ], QA + 1 - 12 );
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}
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} else {
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for( k = 0; k < d; k++ ) {
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a_Q12[ k ] = (opus_int16)silk_RSHIFT_ROUND( a32_QA1[ k ], QA + 1 - 12 ); /* QA+1 -> Q12 */
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}
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}
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for( i = 0; i < MAX_LPC_STABILIZE_ITERATIONS; i++ ) {
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if( silk_LPC_inverse_pred_gain( a_Q12, d ) < SILK_FIX_CONST( 1.0 / MAX_PREDICTION_POWER_GAIN, 30 ) ) {
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/* Prediction coefficients are (too close to) unstable; apply bandwidth expansion */
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/* on the unscaled coefficients, convert to Q12 and measure again */
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silk_bwexpander_32( a32_QA1, d, 65536 - silk_LSHIFT( 2, i ) );
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for( k = 0; k < d; k++ ) {
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a_Q12[ k ] = (opus_int16)silk_RSHIFT_ROUND( a32_QA1[ k ], QA + 1 - 12 ); /* QA+1 -> Q12 */
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}
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} else {
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break;
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}
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}
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}
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