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Alexandre Lision744f7422013-09-25 11:39:37 -04001/***********************************************************************
2Copyright (c) 2006-2011, Skype Limited. All rights reserved.
3Redistribution and use in source and binary forms, with or without
4modification, are permitted provided that the following conditions
5are met:
6- Redistributions of source code must retain the above copyright notice,
7this list of conditions and the following disclaimer.
8- Redistributions in binary form must reproduce the above copyright
9notice, this list of conditions and the following disclaimer in the
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11- Neither the name of Internet Society, IETF or IETF Trust, nor the
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14permission.
15THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS “AS IS”
16AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
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18ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE
19LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR
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24ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
25POSSIBILITY OF SUCH DAMAGE.
26***********************************************************************/
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. */
39static inline silk_float warped_gain(
40 const silk_float *coefs,
41 silk_float lambda,
42 opus_int order
43) {
44 opus_int i;
45 silk_float gain;
46
47 lambda = -lambda;
48 gain = coefs[ order - 1 ];
49 for( i = order - 2; i >= 0; i-- ) {
50 gain = lambda * gain + coefs[ i ];
51 }
52 return (silk_float)( 1.0f / ( 1.0f - lambda * gain ) );
53}
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 */
57static inline void warped_true2monic_coefs(
58 silk_float *coefs_syn,
59 silk_float *coefs_ana,
60 silk_float lambda,
61 silk_float limit,
62 opus_int order
63) {
64 opus_int i, iter, ind = 0;
65 silk_float tmp, maxabs, chirp, gain_syn, gain_ana;
66
67 /* Convert to monic coefficients */
68 for( i = order - 1; i > 0; i-- ) {
69 coefs_syn[ i - 1 ] -= lambda * coefs_syn[ i ];
70 coefs_ana[ i - 1 ] -= lambda * coefs_ana[ i ];
71 }
72 gain_syn = ( 1.0f - lambda * lambda ) / ( 1.0f + lambda * coefs_syn[ 0 ] );
73 gain_ana = ( 1.0f - lambda * lambda ) / ( 1.0f + lambda * coefs_ana[ 0 ] );
74 for( i = 0; i < order; i++ ) {
75 coefs_syn[ i ] *= gain_syn;
76 coefs_ana[ i ] *= gain_ana;
77 }
78
79 /* Limit */
80 for( iter = 0; iter < 10; iter++ ) {
81 /* Find maximum absolute value */
82 maxabs = -1.0f;
83 for( i = 0; i < order; i++ ) {
84 tmp = silk_max( silk_abs_float( coefs_syn[ i ] ), silk_abs_float( coefs_ana[ i ] ) );
85 if( tmp > maxabs ) {
86 maxabs = tmp;
87 ind = i;
88 }
89 }
90 if( maxabs <= limit ) {
91 /* Coefficients are within range - done */
92 return;
93 }
94
95 /* Convert back to true warped coefficients */
96 for( i = 1; i < order; i++ ) {
97 coefs_syn[ i - 1 ] += lambda * coefs_syn[ i ];
98 coefs_ana[ i - 1 ] += lambda * coefs_ana[ i ];
99 }
100 gain_syn = 1.0f / gain_syn;
101 gain_ana = 1.0f / gain_ana;
102 for( i = 0; i < order; i++ ) {
103 coefs_syn[ i ] *= gain_syn;
104 coefs_ana[ i ] *= gain_ana;
105 }
106
107 /* Apply bandwidth expansion */
108 chirp = 0.99f - ( 0.8f + 0.1f * iter ) * ( maxabs - limit ) / ( maxabs * ( ind + 1 ) );
109 silk_bwexpander_FLP( coefs_syn, order, chirp );
110 silk_bwexpander_FLP( coefs_ana, order, chirp );
111
112 /* Convert to monic warped coefficients */
113 for( i = order - 1; i > 0; i-- ) {
114 coefs_syn[ i - 1 ] -= lambda * coefs_syn[ i ];
115 coefs_ana[ i - 1 ] -= lambda * coefs_ana[ i ];
116 }
117 gain_syn = ( 1.0f - lambda * lambda ) / ( 1.0f + lambda * coefs_syn[ 0 ] );
118 gain_ana = ( 1.0f - lambda * lambda ) / ( 1.0f + lambda * coefs_ana[ 0 ] );
119 for( i = 0; i < order; i++ ) {
120 coefs_syn[ i ] *= gain_syn;
121 coefs_ana[ i ] *= gain_ana;
122 }
123 }
124 silk_assert( 0 );
125}
126
127/* Compute noise shaping coefficients and initial gain values */
128void silk_noise_shape_analysis_FLP(
129 silk_encoder_state_FLP *psEnc, /* I/O Encoder state FLP */
130 silk_encoder_control_FLP *psEncCtrl, /* I/O Encoder control FLP */
131 const silk_float *pitch_res, /* I LPC residual from pitch analysis */
132 const silk_float *x /* I Input signal [frame_length + la_shape] */
133)
134{
135 silk_shape_state_FLP *psShapeSt = &psEnc->sShape;
136 opus_int k, nSamples;
137 silk_float SNR_adj_dB, HarmBoost, HarmShapeGain, Tilt;
138 silk_float nrg, pre_nrg, log_energy, log_energy_prev, energy_variation;
139 silk_float delta, BWExp1, BWExp2, gain_mult, gain_add, strength, b, warping;
140 silk_float x_windowed[ SHAPE_LPC_WIN_MAX ];
141 silk_float auto_corr[ MAX_SHAPE_LPC_ORDER + 1 ];
142 const silk_float *x_ptr, *pitch_res_ptr;
143
144 /* Point to start of first LPC analysis block */
145 x_ptr = x - psEnc->sCmn.la_shape;
146
147 /****************/
148 /* GAIN CONTROL */
149 /****************/
150 SNR_adj_dB = psEnc->sCmn.SNR_dB_Q7 * ( 1 / 128.0f );
151
152 /* Input quality is the average of the quality in the lowest two VAD bands */
153 psEncCtrl->input_quality = 0.5f * ( psEnc->sCmn.input_quality_bands_Q15[ 0 ] + psEnc->sCmn.input_quality_bands_Q15[ 1 ] ) * ( 1.0f / 32768.0f );
154
155 /* Coding quality level, between 0.0 and 1.0 */
156 psEncCtrl->coding_quality = silk_sigmoid( 0.25f * ( SNR_adj_dB - 20.0f ) );
157
158 if( psEnc->sCmn.useCBR == 0 ) {
159 /* Reduce coding SNR during low speech activity */
160 b = 1.0f - psEnc->sCmn.speech_activity_Q8 * ( 1.0f / 256.0f );
161 SNR_adj_dB -= BG_SNR_DECR_dB * psEncCtrl->coding_quality * ( 0.5f + 0.5f * psEncCtrl->input_quality ) * b * b;
162 }
163
164 if( psEnc->sCmn.indices.signalType == TYPE_VOICED ) {
165 /* Reduce gains for periodic signals */
166 SNR_adj_dB += HARM_SNR_INCR_dB * psEnc->LTPCorr;
167 } else {
168 /* For unvoiced signals and low-quality input, adjust the quality slower than SNR_dB setting */
169 SNR_adj_dB += ( -0.4f * psEnc->sCmn.SNR_dB_Q7 * ( 1 / 128.0f ) + 6.0f ) * ( 1.0f - psEncCtrl->input_quality );
170 }
171
172 /*************************/
173 /* SPARSENESS PROCESSING */
174 /*************************/
175 /* Set quantizer offset */
176 if( psEnc->sCmn.indices.signalType == TYPE_VOICED ) {
177 /* Initially set to 0; may be overruled in process_gains(..) */
178 psEnc->sCmn.indices.quantOffsetType = 0;
179 psEncCtrl->sparseness = 0.0f;
180 } else {
181 /* Sparseness measure, based on relative fluctuations of energy per 2 milliseconds */
182 nSamples = 2 * psEnc->sCmn.fs_kHz;
183 energy_variation = 0.0f;
184 log_energy_prev = 0.0f;
185 pitch_res_ptr = pitch_res;
186 for( k = 0; k < silk_SMULBB( SUB_FRAME_LENGTH_MS, psEnc->sCmn.nb_subfr ) / 2; k++ ) {
187 nrg = ( silk_float )nSamples + ( silk_float )silk_energy_FLP( pitch_res_ptr, nSamples );
188 log_energy = silk_log2( nrg );
189 if( k > 0 ) {
190 energy_variation += silk_abs_float( log_energy - log_energy_prev );
191 }
192 log_energy_prev = log_energy;
193 pitch_res_ptr += nSamples;
194 }
195 psEncCtrl->sparseness = silk_sigmoid( 0.4f * ( energy_variation - 5.0f ) );
196
197 /* Set quantization offset depending on sparseness measure */
198 if( psEncCtrl->sparseness > SPARSENESS_THRESHOLD_QNT_OFFSET ) {
199 psEnc->sCmn.indices.quantOffsetType = 0;
200 } else {
201 psEnc->sCmn.indices.quantOffsetType = 1;
202 }
203
204 /* Increase coding SNR for sparse signals */
205 SNR_adj_dB += SPARSE_SNR_INCR_dB * ( psEncCtrl->sparseness - 0.5f );
206 }
207
208 /*******************************/
209 /* Control bandwidth expansion */
210 /*******************************/
211 /* More BWE for signals with high prediction gain */
212 strength = FIND_PITCH_WHITE_NOISE_FRACTION * psEncCtrl->predGain; /* between 0.0 and 1.0 */
213 BWExp1 = BWExp2 = BANDWIDTH_EXPANSION / ( 1.0f + strength * strength );
214 delta = LOW_RATE_BANDWIDTH_EXPANSION_DELTA * ( 1.0f - 0.75f * psEncCtrl->coding_quality );
215 BWExp1 -= delta;
216 BWExp2 += delta;
217 /* BWExp1 will be applied after BWExp2, so make it relative */
218 BWExp1 /= BWExp2;
219
220 if( psEnc->sCmn.warping_Q16 > 0 ) {
221 /* Slightly more warping in analysis will move quantization noise up in frequency, where it's better masked */
222 warping = (silk_float)psEnc->sCmn.warping_Q16 / 65536.0f + 0.01f * psEncCtrl->coding_quality;
223 } else {
224 warping = 0.0f;
225 }
226
227 /********************************************/
228 /* Compute noise shaping AR coefs and gains */
229 /********************************************/
230 for( k = 0; k < psEnc->sCmn.nb_subfr; k++ ) {
231 /* Apply window: sine slope followed by flat part followed by cosine slope */
232 opus_int shift, slope_part, flat_part;
233 flat_part = psEnc->sCmn.fs_kHz * 3;
234 slope_part = ( psEnc->sCmn.shapeWinLength - flat_part ) / 2;
235
236 silk_apply_sine_window_FLP( x_windowed, x_ptr, 1, slope_part );
237 shift = slope_part;
238 silk_memcpy( x_windowed + shift, x_ptr + shift, flat_part * sizeof(silk_float) );
239 shift += flat_part;
240 silk_apply_sine_window_FLP( x_windowed + shift, x_ptr + shift, 2, slope_part );
241
242 /* Update pointer: next LPC analysis block */
243 x_ptr += psEnc->sCmn.subfr_length;
244
245 if( psEnc->sCmn.warping_Q16 > 0 ) {
246 /* Calculate warped auto correlation */
247 silk_warped_autocorrelation_FLP( auto_corr, x_windowed, warping,
248 psEnc->sCmn.shapeWinLength, psEnc->sCmn.shapingLPCOrder );
249 } else {
250 /* Calculate regular auto correlation */
251 silk_autocorrelation_FLP( auto_corr, x_windowed, psEnc->sCmn.shapeWinLength, psEnc->sCmn.shapingLPCOrder + 1 );
252 }
253
254 /* Add white noise, as a fraction of energy */
255 auto_corr[ 0 ] += auto_corr[ 0 ] * SHAPE_WHITE_NOISE_FRACTION;
256
257 /* Convert correlations to prediction coefficients, and compute residual energy */
258 nrg = silk_levinsondurbin_FLP( &psEncCtrl->AR2[ k * MAX_SHAPE_LPC_ORDER ], auto_corr, psEnc->sCmn.shapingLPCOrder );
259 psEncCtrl->Gains[ k ] = ( silk_float )sqrt( nrg );
260
261 if( psEnc->sCmn.warping_Q16 > 0 ) {
262 /* Adjust gain for warping */
263 psEncCtrl->Gains[ k ] *= warped_gain( &psEncCtrl->AR2[ k * MAX_SHAPE_LPC_ORDER ], warping, psEnc->sCmn.shapingLPCOrder );
264 }
265
266 /* Bandwidth expansion for synthesis filter shaping */
267 silk_bwexpander_FLP( &psEncCtrl->AR2[ k * MAX_SHAPE_LPC_ORDER ], psEnc->sCmn.shapingLPCOrder, BWExp2 );
268
269 /* Compute noise shaping filter coefficients */
270 silk_memcpy(
271 &psEncCtrl->AR1[ k * MAX_SHAPE_LPC_ORDER ],
272 &psEncCtrl->AR2[ k * MAX_SHAPE_LPC_ORDER ],
273 psEnc->sCmn.shapingLPCOrder * sizeof( silk_float ) );
274
275 /* Bandwidth expansion for analysis filter shaping */
276 silk_bwexpander_FLP( &psEncCtrl->AR1[ k * MAX_SHAPE_LPC_ORDER ], psEnc->sCmn.shapingLPCOrder, BWExp1 );
277
278 /* Ratio of prediction gains, in energy domain */
279 pre_nrg = silk_LPC_inverse_pred_gain_FLP( &psEncCtrl->AR2[ k * MAX_SHAPE_LPC_ORDER ], psEnc->sCmn.shapingLPCOrder );
280 nrg = silk_LPC_inverse_pred_gain_FLP( &psEncCtrl->AR1[ k * MAX_SHAPE_LPC_ORDER ], psEnc->sCmn.shapingLPCOrder );
281 psEncCtrl->GainsPre[ k ] = 1.0f - 0.7f * ( 1.0f - pre_nrg / nrg );
282
283 /* Convert to monic warped prediction coefficients and limit absolute values */
284 warped_true2monic_coefs( &psEncCtrl->AR2[ k * MAX_SHAPE_LPC_ORDER ], &psEncCtrl->AR1[ k * MAX_SHAPE_LPC_ORDER ],
285 warping, 3.999f, psEnc->sCmn.shapingLPCOrder );
286 }
287
288 /*****************/
289 /* Gain tweaking */
290 /*****************/
291 /* Increase gains during low speech activity */
292 gain_mult = (silk_float)pow( 2.0f, -0.16f * SNR_adj_dB );
293 gain_add = (silk_float)pow( 2.0f, 0.16f * MIN_QGAIN_DB );
294 for( k = 0; k < psEnc->sCmn.nb_subfr; k++ ) {
295 psEncCtrl->Gains[ k ] *= gain_mult;
296 psEncCtrl->Gains[ k ] += gain_add;
297 }
298
299 gain_mult = 1.0f + INPUT_TILT + psEncCtrl->coding_quality * HIGH_RATE_INPUT_TILT;
300 for( k = 0; k < psEnc->sCmn.nb_subfr; k++ ) {
301 psEncCtrl->GainsPre[ k ] *= gain_mult;
302 }
303
304 /************************************************/
305 /* Control low-frequency shaping and noise tilt */
306 /************************************************/
307 /* Less low frequency shaping for noisy inputs */
308 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 ) );
309 strength *= psEnc->sCmn.speech_activity_Q8 * ( 1.0f / 256.0f );
310 if( psEnc->sCmn.indices.signalType == TYPE_VOICED ) {
311 /* Reduce low frequencies quantization noise for periodic signals, depending on pitch lag */
312 /*f = 400; freqz([1, -0.98 + 2e-4 * f], [1, -0.97 + 7e-4 * f], 2^12, Fs); axis([0, 1000, -10, 1])*/
313 for( k = 0; k < psEnc->sCmn.nb_subfr; k++ ) {
314 b = 0.2f / psEnc->sCmn.fs_kHz + 3.0f / psEncCtrl->pitchL[ k ];
315 psEncCtrl->LF_MA_shp[ k ] = -1.0f + b;
316 psEncCtrl->LF_AR_shp[ k ] = 1.0f - b - b * strength;
317 }
318 Tilt = - HP_NOISE_COEF -
319 (1 - HP_NOISE_COEF) * HARM_HP_NOISE_COEF * psEnc->sCmn.speech_activity_Q8 * ( 1.0f / 256.0f );
320 } else {
321 b = 1.3f / psEnc->sCmn.fs_kHz;
322 psEncCtrl->LF_MA_shp[ 0 ] = -1.0f + b;
323 psEncCtrl->LF_AR_shp[ 0 ] = 1.0f - b - b * strength * 0.6f;
324 for( k = 1; k < psEnc->sCmn.nb_subfr; k++ ) {
325 psEncCtrl->LF_MA_shp[ k ] = psEncCtrl->LF_MA_shp[ 0 ];
326 psEncCtrl->LF_AR_shp[ k ] = psEncCtrl->LF_AR_shp[ 0 ];
327 }
328 Tilt = -HP_NOISE_COEF;
329 }
330
331 /****************************/
332 /* HARMONIC SHAPING CONTROL */
333 /****************************/
334 /* Control boosting of harmonic frequencies */
335 HarmBoost = LOW_RATE_HARMONIC_BOOST * ( 1.0f - psEncCtrl->coding_quality ) * psEnc->LTPCorr;
336
337 /* More harmonic boost for noisy input signals */
338 HarmBoost += LOW_INPUT_QUALITY_HARMONIC_BOOST * ( 1.0f - psEncCtrl->input_quality );
339
340 if( USE_HARM_SHAPING && psEnc->sCmn.indices.signalType == TYPE_VOICED ) {
341 /* Harmonic noise shaping */
342 HarmShapeGain = HARMONIC_SHAPING;
343
344 /* More harmonic noise shaping for high bitrates or noisy input */
345 HarmShapeGain += HIGH_RATE_OR_LOW_QUALITY_HARMONIC_SHAPING *
346 ( 1.0f - ( 1.0f - psEncCtrl->coding_quality ) * psEncCtrl->input_quality );
347
348 /* Less harmonic noise shaping for less periodic signals */
349 HarmShapeGain *= ( silk_float )sqrt( psEnc->LTPCorr );
350 } else {
351 HarmShapeGain = 0.0f;
352 }
353
354 /*************************/
355 /* Smooth over subframes */
356 /*************************/
357 for( k = 0; k < psEnc->sCmn.nb_subfr; k++ ) {
358 psShapeSt->HarmBoost_smth += SUBFR_SMTH_COEF * ( HarmBoost - psShapeSt->HarmBoost_smth );
359 psEncCtrl->HarmBoost[ k ] = psShapeSt->HarmBoost_smth;
360 psShapeSt->HarmShapeGain_smth += SUBFR_SMTH_COEF * ( HarmShapeGain - psShapeSt->HarmShapeGain_smth );
361 psEncCtrl->HarmShapeGain[ k ] = psShapeSt->HarmShapeGain_smth;
362 psShapeSt->Tilt_smth += SUBFR_SMTH_COEF * ( Tilt - psShapeSt->Tilt_smth );
363 psEncCtrl->Tilt[ k ] = psShapeSt->Tilt_smth;
364 }
365}