Coverage Report

Created: 2026-02-26 07:37

next uncovered line (L), next uncovered region (R), next uncovered branch (B)
/src/opus/silk/float/noise_shape_analysis_FLP.c
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Source
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/***********************************************************************
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Copyright (c) 2006-2011, Skype Limited. All rights reserved.
3
Redistribution and use in source and binary forms, with or without
4
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
12
names of specific contributors, may be used to endorse or promote
13
products derived from this software without specific prior written
14
permission.
15
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
17
IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE
18
ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE
19
LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR
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CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF
21
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
23
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
25
POSSIBILITY OF SUCH DAMAGE.
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***********************************************************************/
27
28
#ifdef HAVE_CONFIG_H
29
#include "config.h"
30
#endif
31
32
#include "main_FLP.h"
33
#include "tuning_parameters.h"
34
35
/* Compute gain to make warped filter coefficients have a zero mean log frequency response on a   */
36
/* non-warped frequency scale. (So that it can be implemented with a minimum-phase monic filter.) */
37
/* Note: A monic filter is one with the first coefficient equal to 1.0. In Silk we omit the first */
38
/* coefficient in an array of coefficients, for monic filters.                                    */
39
static OPUS_INLINE silk_float warped_gain(
40
    const silk_float     *coefs,
41
    silk_float           lambda,
42
    opus_int             order
43
73.3M
) {
44
73.3M
    opus_int   i;
45
73.3M
    silk_float gain;
46
47
73.3M
    lambda = -lambda;
48
73.3M
    gain = coefs[ order - 1 ];
49
1.46G
    for( i = order - 2; i >= 0; i-- ) {
50
1.39G
        gain = lambda * gain + coefs[ i ];
51
1.39G
    }
52
73.3M
    return (silk_float)( 1.0f / ( 1.0f - lambda * gain ) );
53
73.3M
}
54
55
/* Convert warped filter coefficients to monic pseudo-warped coefficients and limit maximum     */
56
/* amplitude of monic warped coefficients by using bandwidth expansion on the true coefficients */
57
static OPUS_INLINE void warped_true2monic_coefs(
58
    silk_float           *coefs,
59
    silk_float           lambda,
60
    silk_float           limit,
61
    opus_int             order
62
73.3M
) {
63
73.3M
    opus_int   i, iter, ind = 0;
64
73.3M
    silk_float tmp, maxabs, chirp, gain;
65
66
    /* Convert to monic coefficients */
67
1.46G
    for( i = order - 1; i > 0; i-- ) {
68
1.39G
        coefs[ i - 1 ] -= lambda * coefs[ i ];
69
1.39G
    }
70
73.3M
    gain = ( 1.0f - lambda * lambda ) / ( 1.0f + lambda * coefs[ 0 ] );
71
1.54G
    for( i = 0; i < order; i++ ) {
72
1.46G
        coefs[ i ] *= gain;
73
1.46G
    }
74
75
    /* Limit */
76
73.3M
    for( iter = 0; iter < 10; iter++ ) {
77
        /* Find maximum absolute value */
78
73.3M
        maxabs = -1.0f;
79
1.54G
        for( i = 0; i < order; i++ ) {
80
1.46G
            tmp = silk_abs_float( coefs[ i ] );
81
1.46G
            if( tmp > maxabs ) {
82
75.2M
                maxabs = tmp;
83
75.2M
                ind = i;
84
75.2M
            }
85
1.46G
        }
86
73.3M
        if( maxabs <= limit ) {
87
            /* Coefficients are within range - done */
88
73.3M
            return;
89
73.3M
        }
90
91
        /* Convert back to true warped coefficients */
92
57.1k
        for( i = 1; i < order; i++ ) {
93
54.4k
            coefs[ i - 1 ] += lambda * coefs[ i ];
94
54.4k
        }
95
2.64k
        gain = 1.0f / gain;
96
59.7k
        for( i = 0; i < order; i++ ) {
97
57.1k
            coefs[ i ] *= gain;
98
57.1k
        }
99
100
        /* Apply bandwidth expansion */
101
2.64k
        chirp = 0.99f - ( 0.8f + 0.1f * iter ) * ( maxabs - limit ) / ( maxabs * ( ind + 1 ) );
102
2.64k
        silk_bwexpander_FLP( coefs, order, chirp );
103
104
        /* Convert to monic warped coefficients */
105
57.1k
        for( i = order - 1; i > 0; i-- ) {
106
54.4k
            coefs[ i - 1 ] -= lambda * coefs[ i ];
107
54.4k
        }
108
2.64k
        gain = ( 1.0f - lambda * lambda ) / ( 1.0f + lambda * coefs[ 0 ] );
109
59.7k
        for( i = 0; i < order; i++ ) {
110
57.1k
            coefs[ i ] *= gain;
111
57.1k
        }
112
2.64k
    }
113
0
    silk_assert( 0 );
114
0
}
115
116
static OPUS_INLINE void limit_coefs(
117
    silk_float           *coefs,
118
    silk_float           limit,
119
    opus_int             order
120
120M
) {
121
120M
    opus_int   i, iter, ind = 0;
122
120M
    silk_float tmp, maxabs, chirp;
123
124
120M
    for( iter = 0; iter < 10; iter++ ) {
125
        /* Find maximum absolute value */
126
120M
        maxabs = -1.0f;
127
1.63G
        for( i = 0; i < order; i++ ) {
128
1.51G
            tmp = silk_abs_float( coefs[ i ] );
129
1.51G
            if( tmp > maxabs ) {
130
141M
                maxabs = tmp;
131
141M
                ind = i;
132
141M
            }
133
1.51G
        }
134
120M
        if( maxabs <= limit ) {
135
            /* Coefficients are within range - done */
136
120M
            return;
137
120M
        }
138
139
        /* Apply bandwidth expansion */
140
4.93k
        chirp = 0.99f - ( 0.8f + 0.1f * iter ) * ( maxabs - limit ) / ( maxabs * ( ind + 1 ) );
141
4.93k
        silk_bwexpander_FLP( coefs, order, chirp );
142
4.93k
    }
143
0
    silk_assert( 0 );
144
0
}
145
146
/* Compute noise shaping coefficients and initial gain values */
147
void silk_noise_shape_analysis_FLP(
148
    silk_encoder_state_FLP          *psEnc,                             /* I/O  Encoder state FLP                           */
149
    silk_encoder_control_FLP        *psEncCtrl,                         /* I/O  Encoder control FLP                         */
150
    const silk_float                *pitch_res,                         /* I    LPC residual from pitch analysis            */
151
    const silk_float                *x                                  /* I    Input signal [frame_length + la_shape]      */
152
)
153
57.9M
{
154
57.9M
    silk_shape_state_FLP *psShapeSt = &psEnc->sShape;
155
57.9M
    opus_int     k, nSamples, nSegs;
156
57.9M
    silk_float   SNR_adj_dB, HarmShapeGain, Tilt;
157
57.9M
    silk_float   nrg, log_energy, log_energy_prev, energy_variation;
158
57.9M
    silk_float   BWExp, gain_mult, gain_add, strength, b, warping;
159
57.9M
    silk_float   x_windowed[ SHAPE_LPC_WIN_MAX ];
160
57.9M
    silk_float   auto_corr[ MAX_SHAPE_LPC_ORDER + 1 ];
161
57.9M
    silk_float   rc[ MAX_SHAPE_LPC_ORDER + 1 ];
162
57.9M
    const silk_float *x_ptr, *pitch_res_ptr;
163
164
    /* Point to start of first LPC analysis block */
165
57.9M
    x_ptr = x - psEnc->sCmn.la_shape;
166
167
    /****************/
168
    /* GAIN CONTROL */
169
    /****************/
170
57.9M
    SNR_adj_dB = psEnc->sCmn.SNR_dB_Q7 * ( 1 / 128.0f );
171
172
    /* Input quality is the average of the quality in the lowest two VAD bands */
173
57.9M
    psEncCtrl->input_quality = 0.5f * ( psEnc->sCmn.input_quality_bands_Q15[ 0 ] + psEnc->sCmn.input_quality_bands_Q15[ 1 ] ) * ( 1.0f / 32768.0f );
174
175
    /* Coding quality level, between 0.0 and 1.0 */
176
57.9M
    psEncCtrl->coding_quality = silk_sigmoid( 0.25f * ( SNR_adj_dB - 20.0f ) );
177
178
57.9M
    if( psEnc->sCmn.useCBR == 0 ) {
179
        /* Reduce coding SNR during low speech activity */
180
22.8M
        b = 1.0f - psEnc->sCmn.speech_activity_Q8 * ( 1.0f /  256.0f );
181
22.8M
        SNR_adj_dB -= BG_SNR_DECR_dB * psEncCtrl->coding_quality * ( 0.5f + 0.5f * psEncCtrl->input_quality ) * b * b;
182
22.8M
    }
183
184
57.9M
    if( psEnc->sCmn.indices.signalType == TYPE_VOICED ) {
185
        /* Reduce gains for periodic signals */
186
476k
        SNR_adj_dB += HARM_SNR_INCR_dB * psEnc->LTPCorr;
187
57.5M
    } else {
188
        /* For unvoiced signals and low-quality input, adjust the quality slower than SNR_dB setting */
189
57.5M
        SNR_adj_dB += ( -0.4f * psEnc->sCmn.SNR_dB_Q7 * ( 1 / 128.0f ) + 6.0f ) * ( 1.0f - psEncCtrl->input_quality );
190
57.5M
    }
191
192
    /*************************/
193
    /* SPARSENESS PROCESSING */
194
    /*************************/
195
    /* Set quantizer offset */
196
57.9M
    if( psEnc->sCmn.indices.signalType == TYPE_VOICED ) {
197
        /* Initially set to 0; may be overruled in process_gains(..) */
198
476k
        psEnc->sCmn.indices.quantOffsetType = 0;
199
57.5M
    } else {
200
        /* Sparseness measure, based on relative fluctuations of energy per 2 milliseconds */
201
57.5M
        nSamples = 2 * psEnc->sCmn.fs_kHz;
202
57.5M
        energy_variation = 0.0f;
203
57.5M
        log_energy_prev  = 0.0f;
204
57.5M
        pitch_res_ptr = pitch_res;
205
57.5M
        nSegs = silk_SMULBB( SUB_FRAME_LENGTH_MS, psEnc->sCmn.nb_subfr ) / 2;
206
537M
        for( k = 0; k < nSegs; k++ ) {
207
479M
            nrg = ( silk_float )nSamples + ( silk_float )silk_energy_FLP( pitch_res_ptr, nSamples );
208
479M
            log_energy = silk_log2( nrg );
209
479M
            if( k > 0 ) {
210
422M
                energy_variation += silk_abs_float( log_energy - log_energy_prev );
211
422M
            }
212
479M
            log_energy_prev = log_energy;
213
479M
            pitch_res_ptr += nSamples;
214
479M
        }
215
216
        /* Set quantization offset depending on sparseness measure */
217
57.5M
        if( energy_variation > ENERGY_VARIATION_THRESHOLD_QNT_OFFSET * (nSegs-1) ) {
218
798k
            psEnc->sCmn.indices.quantOffsetType = 0;
219
56.7M
        } else {
220
56.7M
            psEnc->sCmn.indices.quantOffsetType = 1;
221
56.7M
        }
222
57.5M
    }
223
224
    /*******************************/
225
    /* Control bandwidth expansion */
226
    /*******************************/
227
    /* More BWE for signals with high prediction gain */
228
57.9M
    strength = FIND_PITCH_WHITE_NOISE_FRACTION * psEncCtrl->predGain;           /* between 0.0 and 1.0 */
229
57.9M
    BWExp = BANDWIDTH_EXPANSION / ( 1.0f + strength * strength );
230
231
    /* Slightly more warping in analysis will move quantization noise up in frequency, where it's better masked */
232
57.9M
    warping = (silk_float)psEnc->sCmn.warping_Q16 / 65536.0f + 0.01f * psEncCtrl->coding_quality;
233
234
    /********************************************/
235
    /* Compute noise shaping AR coefs and gains */
236
    /********************************************/
237
251M
    for( k = 0; k < psEnc->sCmn.nb_subfr; k++ ) {
238
        /* Apply window: sine slope followed by flat part followed by cosine slope */
239
193M
        opus_int shift, slope_part, flat_part;
240
193M
        flat_part = psEnc->sCmn.fs_kHz * 3;
241
193M
        slope_part = ( psEnc->sCmn.shapeWinLength - flat_part ) / 2;
242
243
193M
        silk_apply_sine_window_FLP( x_windowed, x_ptr, 1, slope_part );
244
193M
        shift = slope_part;
245
193M
        silk_memcpy( x_windowed + shift, x_ptr + shift, flat_part * sizeof(silk_float) );
246
193M
        shift += flat_part;
247
193M
        silk_apply_sine_window_FLP( x_windowed + shift, x_ptr + shift, 2, slope_part );
248
249
        /* Update pointer: next LPC analysis block */
250
193M
        x_ptr += psEnc->sCmn.subfr_length;
251
252
193M
        if( psEnc->sCmn.warping_Q16 > 0 ) {
253
            /* Calculate warped auto correlation */
254
73.3M
            silk_warped_autocorrelation_FLP( auto_corr, x_windowed, warping,
255
73.3M
                psEnc->sCmn.shapeWinLength, psEnc->sCmn.shapingLPCOrder );
256
120M
        } else {
257
            /* Calculate regular auto correlation */
258
120M
            silk_autocorrelation_FLP( auto_corr, x_windowed, psEnc->sCmn.shapeWinLength, psEnc->sCmn.shapingLPCOrder + 1, psEnc->sCmn.arch );
259
120M
        }
260
261
        /* Add white noise, as a fraction of energy */
262
193M
        auto_corr[ 0 ] += auto_corr[ 0 ] * SHAPE_WHITE_NOISE_FRACTION + 1.0f;
263
264
        /* Convert correlations to prediction coefficients, and compute residual energy */
265
193M
        nrg = silk_schur_FLP( rc, auto_corr, psEnc->sCmn.shapingLPCOrder );
266
193M
        silk_k2a_FLP( &psEncCtrl->AR[ k * MAX_SHAPE_LPC_ORDER ], rc, psEnc->sCmn.shapingLPCOrder );
267
193M
        psEncCtrl->Gains[ k ] = ( silk_float )sqrt( nrg );
268
269
193M
        if( psEnc->sCmn.warping_Q16 > 0 ) {
270
            /* Adjust gain for warping */
271
73.3M
            psEncCtrl->Gains[ k ] *= warped_gain( &psEncCtrl->AR[ k * MAX_SHAPE_LPC_ORDER ], warping, psEnc->sCmn.shapingLPCOrder );
272
73.3M
        }
273
274
        /* Bandwidth expansion for synthesis filter shaping */
275
193M
        silk_bwexpander_FLP( &psEncCtrl->AR[ k * MAX_SHAPE_LPC_ORDER ], psEnc->sCmn.shapingLPCOrder, BWExp );
276
277
193M
        if( psEnc->sCmn.warping_Q16 > 0 ) {
278
            /* Convert to monic warped prediction coefficients and limit absolute values */
279
73.3M
            warped_true2monic_coefs( &psEncCtrl->AR[ k * MAX_SHAPE_LPC_ORDER ], warping, 3.999f, psEnc->sCmn.shapingLPCOrder );
280
120M
        } else {
281
            /* Limit absolute values */
282
120M
            limit_coefs( &psEncCtrl->AR[ k * MAX_SHAPE_LPC_ORDER ], 3.999f, psEnc->sCmn.shapingLPCOrder );
283
120M
        }
284
193M
    }
285
286
    /*****************/
287
    /* Gain tweaking */
288
    /*****************/
289
    /* Increase gains during low speech activity */
290
57.9M
    gain_mult = (silk_float)pow( 2.0f, -0.16f * SNR_adj_dB );
291
57.9M
    gain_add  = (silk_float)pow( 2.0f,  0.16f * MIN_QGAIN_DB );
292
251M
    for( k = 0; k < psEnc->sCmn.nb_subfr; k++ ) {
293
193M
        psEncCtrl->Gains[ k ] *= gain_mult;
294
193M
        psEncCtrl->Gains[ k ] += gain_add;
295
193M
    }
296
297
    /************************************************/
298
    /* Control low-frequency shaping and noise tilt */
299
    /************************************************/
300
    /* Less low frequency shaping for noisy inputs */
301
57.9M
    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 ) );
302
57.9M
    strength *= psEnc->sCmn.speech_activity_Q8 * ( 1.0f /  256.0f );
303
57.9M
    if( psEnc->sCmn.indices.signalType == TYPE_VOICED ) {
304
        /* Reduce low frequencies quantization noise for periodic signals, depending on pitch lag */
305
        /*f = 400; freqz([1, -0.98 + 2e-4 * f], [1, -0.97 + 7e-4 * f], 2^12, Fs); axis([0, 1000, -10, 1])*/
306
2.18M
        for( k = 0; k < psEnc->sCmn.nb_subfr; k++ ) {
307
1.70M
            b = 0.2f / psEnc->sCmn.fs_kHz + 3.0f / psEncCtrl->pitchL[ k ];
308
1.70M
            psEncCtrl->LF_MA_shp[ k ] = -1.0f + b;
309
1.70M
            psEncCtrl->LF_AR_shp[ k ] =  1.0f - b - b * strength;
310
1.70M
        }
311
476k
        Tilt = - HP_NOISE_COEF -
312
476k
            (1 - HP_NOISE_COEF) * HARM_HP_NOISE_COEF * psEnc->sCmn.speech_activity_Q8 * ( 1.0f /  256.0f );
313
57.5M
    } else {
314
57.5M
        b = 1.3f / psEnc->sCmn.fs_kHz;
315
57.5M
        psEncCtrl->LF_MA_shp[ 0 ] = -1.0f + b;
316
57.5M
        psEncCtrl->LF_AR_shp[ 0 ] =  1.0f - b - b * strength * 0.6f;
317
191M
        for( k = 1; k < psEnc->sCmn.nb_subfr; k++ ) {
318
134M
            psEncCtrl->LF_MA_shp[ k ] = psEncCtrl->LF_MA_shp[ 0 ];
319
134M
            psEncCtrl->LF_AR_shp[ k ] = psEncCtrl->LF_AR_shp[ 0 ];
320
134M
        }
321
57.5M
        Tilt = -HP_NOISE_COEF;
322
57.5M
    }
323
324
    /****************************/
325
    /* HARMONIC SHAPING CONTROL */
326
    /****************************/
327
57.9M
    if( USE_HARM_SHAPING && psEnc->sCmn.indices.signalType == TYPE_VOICED ) {
328
        /* Harmonic noise shaping */
329
476k
        HarmShapeGain = HARMONIC_SHAPING;
330
331
        /* More harmonic noise shaping for high bitrates or noisy input */
332
476k
        HarmShapeGain += HIGH_RATE_OR_LOW_QUALITY_HARMONIC_SHAPING *
333
476k
            ( 1.0f - ( 1.0f - psEncCtrl->coding_quality ) * psEncCtrl->input_quality );
334
335
        /* Less harmonic noise shaping for less periodic signals */
336
476k
        HarmShapeGain *= ( silk_float )sqrt( psEnc->LTPCorr );
337
57.5M
    } else {
338
57.5M
        HarmShapeGain = 0.0f;
339
57.5M
    }
340
341
    /*************************/
342
    /* Smooth over subframes */
343
    /*************************/
344
251M
    for( k = 0; k < psEnc->sCmn.nb_subfr; k++ ) {
345
193M
        psShapeSt->HarmShapeGain_smth += SUBFR_SMTH_COEF * ( HarmShapeGain - psShapeSt->HarmShapeGain_smth );
346
193M
        psEncCtrl->HarmShapeGain[ k ]  = psShapeSt->HarmShapeGain_smth;
347
193M
        psShapeSt->Tilt_smth          += SUBFR_SMTH_COEF * ( Tilt - psShapeSt->Tilt_smth );
348
193M
        psEncCtrl->Tilt[ k ]           = psShapeSt->Tilt_smth;
349
193M
    }
350
57.9M
}