blob: 0f9894e9fc305ee2658431b42f630ebd0cfb3e02 [file] [log] [blame]
/*
* Copyright (c) 2012 The WebRTC project authors. All Rights Reserved.
*
* Use of this source code is governed by a BSD-style license
* that can be found in the LICENSE file in the root of the source
* tree. An additional intellectual property rights grant can be found
* in the file PATENTS. All contributing project authors may
* be found in the AUTHORS file in the root of the source tree.
*/
#include "webrtc/modules/audio_processing/ns/include/noise_suppression_x.h"
#include <assert.h>
#include <math.h>
#include <stdlib.h>
#include <string.h>
#include "webrtc/common_audio/signal_processing/include/real_fft.h"
#include "webrtc/modules/audio_processing/ns/nsx_core.h"
#include "webrtc/system_wrappers/interface/cpu_features_wrapper.h"
#if (defined WEBRTC_DETECT_NEON || defined WEBRTC_HAS_NEON)
/* Tables are defined in ARM assembly files. */
extern const int16_t WebRtcNsx_kLogTable[9];
extern const int16_t WebRtcNsx_kCounterDiv[201];
extern const int16_t WebRtcNsx_kLogTableFrac[256];
#else
static const int16_t WebRtcNsx_kLogTable[9] = {
0, 177, 355, 532, 710, 887, 1065, 1242, 1420
};
static const int16_t WebRtcNsx_kCounterDiv[201] = {
32767, 16384, 10923, 8192, 6554, 5461, 4681, 4096, 3641, 3277, 2979, 2731,
2521, 2341, 2185, 2048, 1928, 1820, 1725, 1638, 1560, 1489, 1425, 1365, 1311,
1260, 1214, 1170, 1130, 1092, 1057, 1024, 993, 964, 936, 910, 886, 862, 840,
819, 799, 780, 762, 745, 728, 712, 697, 683, 669, 655, 643, 630, 618, 607,
596, 585, 575, 565, 555, 546, 537, 529, 520, 512, 504, 496, 489, 482, 475,
468, 462, 455, 449, 443, 437, 431, 426, 420, 415, 410, 405, 400, 395, 390,
386, 381, 377, 372, 368, 364, 360, 356, 352, 349, 345, 341, 338, 334, 331,
328, 324, 321, 318, 315, 312, 309, 306, 303, 301, 298, 295, 293, 290, 287,
285, 282, 280, 278, 275, 273, 271, 269, 266, 264, 262, 260, 258, 256, 254,
252, 250, 248, 246, 245, 243, 241, 239, 237, 236, 234, 232, 231, 229, 228,
226, 224, 223, 221, 220, 218, 217, 216, 214, 213, 211, 210, 209, 207, 206,
205, 204, 202, 201, 200, 199, 197, 196, 195, 194, 193, 192, 191, 189, 188,
187, 186, 185, 184, 183, 182, 181, 180, 179, 178, 177, 176, 175, 174, 173,
172, 172, 171, 170, 169, 168, 167, 166, 165, 165, 164, 163
};
static const int16_t WebRtcNsx_kLogTableFrac[256] = {
0, 1, 3, 4, 6, 7, 9, 10, 11, 13, 14, 16, 17, 18, 20, 21,
22, 24, 25, 26, 28, 29, 30, 32, 33, 34, 36, 37, 38, 40, 41, 42,
44, 45, 46, 47, 49, 50, 51, 52, 54, 55, 56, 57, 59, 60, 61, 62,
63, 65, 66, 67, 68, 69, 71, 72, 73, 74, 75, 77, 78, 79, 80, 81,
82, 84, 85, 86, 87, 88, 89, 90, 92, 93, 94, 95, 96, 97, 98, 99,
100, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 116,
117, 118, 119, 120, 121, 122, 123, 124, 125, 126, 127, 128, 129, 130, 131,
132, 133, 134, 135, 136, 137, 138, 139, 140, 141, 142, 143, 144, 145, 146,
147, 148, 149, 150, 151, 152, 153, 154, 155, 155, 156, 157, 158, 159, 160,
161, 162, 163, 164, 165, 166, 167, 168, 169, 169, 170, 171, 172, 173, 174,
175, 176, 177, 178, 178, 179, 180, 181, 182, 183, 184, 185, 185, 186, 187,
188, 189, 190, 191, 192, 192, 193, 194, 195, 196, 197, 198, 198, 199, 200,
201, 202, 203, 203, 204, 205, 206, 207, 208, 208, 209, 210, 211, 212, 212,
213, 214, 215, 216, 216, 217, 218, 219, 220, 220, 221, 222, 223, 224, 224,
225, 226, 227, 228, 228, 229, 230, 231, 231, 232, 233, 234, 234, 235, 236,
237, 238, 238, 239, 240, 241, 241, 242, 243, 244, 244, 245, 246, 247, 247,
248, 249, 249, 250, 251, 252, 252, 253, 254, 255, 255
};
#endif // WEBRTC_DETECT_NEON || WEBRTC_HAS_NEON
// Skip first frequency bins during estimation. (0 <= value < 64)
static const int kStartBand = 5;
// hybrib Hanning & flat window
static const int16_t kBlocks80w128x[128] = {
0, 536, 1072, 1606, 2139, 2669, 3196, 3720, 4240, 4756, 5266,
5771, 6270, 6762, 7246, 7723, 8192, 8652, 9102, 9543, 9974, 10394,
10803, 11200, 11585, 11958, 12318, 12665, 12998, 13318, 13623, 13913, 14189,
14449, 14694, 14924, 15137, 15334, 15515, 15679, 15826, 15956, 16069, 16165,
16244, 16305, 16349, 16375, 16384, 16384, 16384, 16384, 16384, 16384, 16384,
16384, 16384, 16384, 16384, 16384, 16384, 16384, 16384, 16384, 16384, 16384,
16384, 16384, 16384, 16384, 16384, 16384, 16384, 16384, 16384, 16384, 16384,
16384, 16384, 16384, 16384, 16375, 16349, 16305, 16244, 16165, 16069, 15956,
15826, 15679, 15515, 15334, 15137, 14924, 14694, 14449, 14189, 13913, 13623,
13318, 12998, 12665, 12318, 11958, 11585, 11200, 10803, 10394, 9974, 9543,
9102, 8652, 8192, 7723, 7246, 6762, 6270, 5771, 5266, 4756, 4240,
3720, 3196, 2669, 2139, 1606, 1072, 536
};
// hybrib Hanning & flat window
static const int16_t kBlocks160w256x[256] = {
0, 268, 536, 804, 1072, 1339, 1606, 1872,
2139, 2404, 2669, 2933, 3196, 3459, 3720, 3981,
4240, 4499, 4756, 5012, 5266, 5520, 5771, 6021,
6270, 6517, 6762, 7005, 7246, 7486, 7723, 7959,
8192, 8423, 8652, 8878, 9102, 9324, 9543, 9760,
9974, 10185, 10394, 10600, 10803, 11003, 11200, 11394,
11585, 11773, 11958, 12140, 12318, 12493, 12665, 12833,
12998, 13160, 13318, 13472, 13623, 13770, 13913, 14053,
14189, 14321, 14449, 14574, 14694, 14811, 14924, 15032,
15137, 15237, 15334, 15426, 15515, 15599, 15679, 15754,
15826, 15893, 15956, 16015, 16069, 16119, 16165, 16207,
16244, 16277, 16305, 16329, 16349, 16364, 16375, 16382,
16384, 16384, 16384, 16384, 16384, 16384, 16384, 16384,
16384, 16384, 16384, 16384, 16384, 16384, 16384, 16384,
16384, 16384, 16384, 16384, 16384, 16384, 16384, 16384,
16384, 16384, 16384, 16384, 16384, 16384, 16384, 16384,
16384, 16384, 16384, 16384, 16384, 16384, 16384, 16384,
16384, 16384, 16384, 16384, 16384, 16384, 16384, 16384,
16384, 16384, 16384, 16384, 16384, 16384, 16384, 16384,
16384, 16384, 16384, 16384, 16384, 16384, 16384, 16384,
16384, 16382, 16375, 16364, 16349, 16329, 16305, 16277,
16244, 16207, 16165, 16119, 16069, 16015, 15956, 15893,
15826, 15754, 15679, 15599, 15515, 15426, 15334, 15237,
15137, 15032, 14924, 14811, 14694, 14574, 14449, 14321,
14189, 14053, 13913, 13770, 13623, 13472, 13318, 13160,
12998, 12833, 12665, 12493, 12318, 12140, 11958, 11773,
11585, 11394, 11200, 11003, 10803, 10600, 10394, 10185,
9974, 9760, 9543, 9324, 9102, 8878, 8652, 8423,
8192, 7959, 7723, 7486, 7246, 7005, 6762, 6517,
6270, 6021, 5771, 5520, 5266, 5012, 4756, 4499,
4240, 3981, 3720, 3459, 3196, 2933, 2669, 2404,
2139, 1872, 1606, 1339, 1072, 804, 536, 268
};
// Gain factor1 table: Input value in Q8 and output value in Q13
// original floating point code
// if (gain > blim) {
// factor1 = 1.0 + 1.3 * (gain - blim);
// if (gain * factor1 > 1.0) {
// factor1 = 1.0 / gain;
// }
// } else {
// factor1 = 1.0;
// }
static const int16_t kFactor1Table[257] = {
8192, 8192, 8192, 8192, 8192, 8192, 8192,
8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192,
8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192,
8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192,
8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192,
8192, 8192, 8233, 8274, 8315, 8355, 8396, 8436, 8475, 8515, 8554, 8592, 8631, 8669,
8707, 8745, 8783, 8820, 8857, 8894, 8931, 8967, 9003, 9039, 9075, 9111, 9146, 9181,
9216, 9251, 9286, 9320, 9354, 9388, 9422, 9456, 9489, 9523, 9556, 9589, 9622, 9655,
9687, 9719, 9752, 9784, 9816, 9848, 9879, 9911, 9942, 9973, 10004, 10035, 10066,
10097, 10128, 10158, 10188, 10218, 10249, 10279, 10308, 10338, 10368, 10397, 10426,
10456, 10485, 10514, 10543, 10572, 10600, 10629, 10657, 10686, 10714, 10742, 10770,
10798, 10826, 10854, 10882, 10847, 10810, 10774, 10737, 10701, 10666, 10631, 10596,
10562, 10527, 10494, 10460, 10427, 10394, 10362, 10329, 10297, 10266, 10235, 10203,
10173, 10142, 10112, 10082, 10052, 10023, 9994, 9965, 9936, 9908, 9879, 9851, 9824,
9796, 9769, 9742, 9715, 9689, 9662, 9636, 9610, 9584, 9559, 9534, 9508, 9484, 9459,
9434, 9410, 9386, 9362, 9338, 9314, 9291, 9268, 9245, 9222, 9199, 9176, 9154, 9132,
9110, 9088, 9066, 9044, 9023, 9002, 8980, 8959, 8939, 8918, 8897, 8877, 8857, 8836,
8816, 8796, 8777, 8757, 8738, 8718, 8699, 8680, 8661, 8642, 8623, 8605, 8586, 8568,
8550, 8532, 8514, 8496, 8478, 8460, 8443, 8425, 8408, 8391, 8373, 8356, 8339, 8323,
8306, 8289, 8273, 8256, 8240, 8224, 8208, 8192
};
// For Factor2 tables
// original floating point code
// if (gain > blim) {
// factor2 = 1.0;
// } else {
// factor2 = 1.0 - 0.3 * (blim - gain);
// if (gain <= inst->denoiseBound) {
// factor2 = 1.0 - 0.3 * (blim - inst->denoiseBound);
// }
// }
//
// Gain factor table: Input value in Q8 and output value in Q13
static const int16_t kFactor2Aggressiveness1[257] = {
7577, 7577, 7577, 7577, 7577, 7577,
7577, 7577, 7577, 7577, 7577, 7577, 7577, 7577, 7577, 7577, 7577, 7596, 7614, 7632,
7650, 7667, 7683, 7699, 7715, 7731, 7746, 7761, 7775, 7790, 7804, 7818, 7832, 7845,
7858, 7871, 7884, 7897, 7910, 7922, 7934, 7946, 7958, 7970, 7982, 7993, 8004, 8016,
8027, 8038, 8049, 8060, 8070, 8081, 8091, 8102, 8112, 8122, 8132, 8143, 8152, 8162,
8172, 8182, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192,
8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192,
8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192,
8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192,
8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192,
8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192,
8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192,
8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192,
8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192,
8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192,
8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192,
8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192,
8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192,
8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192
};
// Gain factor table: Input value in Q8 and output value in Q13
static const int16_t kFactor2Aggressiveness2[257] = {
7270, 7270, 7270, 7270, 7270, 7306,
7339, 7369, 7397, 7424, 7448, 7472, 7495, 7517, 7537, 7558, 7577, 7596, 7614, 7632,
7650, 7667, 7683, 7699, 7715, 7731, 7746, 7761, 7775, 7790, 7804, 7818, 7832, 7845,
7858, 7871, 7884, 7897, 7910, 7922, 7934, 7946, 7958, 7970, 7982, 7993, 8004, 8016,
8027, 8038, 8049, 8060, 8070, 8081, 8091, 8102, 8112, 8122, 8132, 8143, 8152, 8162,
8172, 8182, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192,
8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192,
8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192,
8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192,
8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192,
8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192,
8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192,
8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192,
8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192,
8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192,
8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192,
8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192,
8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192,
8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192
};
// Gain factor table: Input value in Q8 and output value in Q13
static const int16_t kFactor2Aggressiveness3[257] = {
7184, 7184, 7184, 7229, 7270, 7306,
7339, 7369, 7397, 7424, 7448, 7472, 7495, 7517, 7537, 7558, 7577, 7596, 7614, 7632,
7650, 7667, 7683, 7699, 7715, 7731, 7746, 7761, 7775, 7790, 7804, 7818, 7832, 7845,
7858, 7871, 7884, 7897, 7910, 7922, 7934, 7946, 7958, 7970, 7982, 7993, 8004, 8016,
8027, 8038, 8049, 8060, 8070, 8081, 8091, 8102, 8112, 8122, 8132, 8143, 8152, 8162,
8172, 8182, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192,
8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192,
8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192,
8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192,
8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192,
8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192,
8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192,
8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192,
8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192,
8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192,
8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192,
8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192,
8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192,
8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192, 8192
};
// sum of log2(i) from table index to inst->anaLen2 in Q5
// Note that the first table value is invalid, since log2(0) = -infinity
static const int16_t kSumLogIndex[66] = {
0, 22917, 22917, 22885, 22834, 22770, 22696, 22613,
22524, 22428, 22326, 22220, 22109, 21994, 21876, 21754,
21629, 21501, 21370, 21237, 21101, 20963, 20822, 20679,
20535, 20388, 20239, 20089, 19937, 19783, 19628, 19470,
19312, 19152, 18991, 18828, 18664, 18498, 18331, 18164,
17994, 17824, 17653, 17480, 17306, 17132, 16956, 16779,
16602, 16423, 16243, 16063, 15881, 15699, 15515, 15331,
15146, 14960, 14774, 14586, 14398, 14209, 14019, 13829,
13637, 13445
};
// sum of log2(i)^2 from table index to inst->anaLen2 in Q2
// Note that the first table value is invalid, since log2(0) = -infinity
static const int16_t kSumSquareLogIndex[66] = {
0, 16959, 16959, 16955, 16945, 16929, 16908, 16881,
16850, 16814, 16773, 16729, 16681, 16630, 16575, 16517,
16456, 16392, 16325, 16256, 16184, 16109, 16032, 15952,
15870, 15786, 15700, 15612, 15521, 15429, 15334, 15238,
15140, 15040, 14938, 14834, 14729, 14622, 14514, 14404,
14292, 14179, 14064, 13947, 13830, 13710, 13590, 13468,
13344, 13220, 13094, 12966, 12837, 12707, 12576, 12444,
12310, 12175, 12039, 11902, 11763, 11624, 11483, 11341,
11198, 11054
};
// log2(table index) in Q12
// Note that the first table value is invalid, since log2(0) = -infinity
static const int16_t kLogIndex[129] = {
0, 0, 4096, 6492, 8192, 9511, 10588, 11499,
12288, 12984, 13607, 14170, 14684, 15157, 15595, 16003,
16384, 16742, 17080, 17400, 17703, 17991, 18266, 18529,
18780, 19021, 19253, 19476, 19691, 19898, 20099, 20292,
20480, 20662, 20838, 21010, 21176, 21338, 21496, 21649,
21799, 21945, 22087, 22226, 22362, 22495, 22625, 22752,
22876, 22998, 23117, 23234, 23349, 23462, 23572, 23680,
23787, 23892, 23994, 24095, 24195, 24292, 24388, 24483,
24576, 24668, 24758, 24847, 24934, 25021, 25106, 25189,
25272, 25354, 25434, 25513, 25592, 25669, 25745, 25820,
25895, 25968, 26041, 26112, 26183, 26253, 26322, 26390,
26458, 26525, 26591, 26656, 26721, 26784, 26848, 26910,
26972, 27033, 27094, 27154, 27213, 27272, 27330, 27388,
27445, 27502, 27558, 27613, 27668, 27722, 27776, 27830,
27883, 27935, 27988, 28039, 28090, 28141, 28191, 28241,
28291, 28340, 28388, 28437, 28484, 28532, 28579, 28626,
28672
};
// determinant of estimation matrix in Q0 corresponding to the log2 tables above
// Note that the first table value is invalid, since log2(0) = -infinity
static const int16_t kDeterminantEstMatrix[66] = {
0, 29814, 25574, 22640, 20351, 18469, 16873, 15491,
14277, 13199, 12233, 11362, 10571, 9851, 9192, 8587,
8030, 7515, 7038, 6596, 6186, 5804, 5448, 5115,
4805, 4514, 4242, 3988, 3749, 3524, 3314, 3116,
2930, 2755, 2590, 2435, 2289, 2152, 2022, 1900,
1785, 1677, 1575, 1478, 1388, 1302, 1221, 1145,
1073, 1005, 942, 881, 825, 771, 721, 674,
629, 587, 547, 510, 475, 442, 411, 382,
355, 330
};
// Update the noise estimation information.
static void UpdateNoiseEstimate(NoiseSuppressionFixedC* inst, int offset) {
int32_t tmp32no1 = 0;
int32_t tmp32no2 = 0;
int16_t tmp16 = 0;
const int16_t kExp2Const = 11819; // Q13
int i = 0;
tmp16 = WebRtcSpl_MaxValueW16(inst->noiseEstLogQuantile + offset,
inst->magnLen);
// Guarantee a Q-domain as high as possible and still fit in int16
inst->qNoise = 14 - (int) WEBRTC_SPL_MUL_16_16_RSFT_WITH_ROUND(
kExp2Const, tmp16, 21);
for (i = 0; i < inst->magnLen; i++) {
// inst->quantile[i]=exp(inst->lquantile[offset+i]);
// in Q21
tmp32no2 = kExp2Const * inst->noiseEstLogQuantile[offset + i];
tmp32no1 = (0x00200000 | (tmp32no2 & 0x001FFFFF)); // 2^21 + frac
tmp16 = (int16_t)(tmp32no2 >> 21);
tmp16 -= 21;// shift 21 to get result in Q0
tmp16 += (int16_t) inst->qNoise; //shift to get result in Q(qNoise)
if (tmp16 < 0) {
tmp32no1 >>= -tmp16;
} else {
tmp32no1 <<= tmp16;
}
inst->noiseEstQuantile[i] = WebRtcSpl_SatW32ToW16(tmp32no1);
}
}
// Noise Estimation
static void NoiseEstimationC(NoiseSuppressionFixedC* inst,
uint16_t* magn,
uint32_t* noise,
int16_t* q_noise) {
int16_t lmagn[HALF_ANAL_BLOCKL], counter, countDiv;
int16_t countProd, delta, zeros, frac;
int16_t log2, tabind, logval, tmp16, tmp16no1, tmp16no2;
const int16_t log2_const = 22713; // Q15
const int16_t width_factor = 21845;
int i, s, offset;
tabind = inst->stages - inst->normData;
assert(tabind < 9);
assert(tabind > -9);
if (tabind < 0) {
logval = -WebRtcNsx_kLogTable[-tabind];
} else {
logval = WebRtcNsx_kLogTable[tabind];
}
// lmagn(i)=log(magn(i))=log(2)*log2(magn(i))
// magn is in Q(-stages), and the real lmagn values are:
// real_lmagn(i)=log(magn(i)*2^stages)=log(magn(i))+log(2^stages)
// lmagn in Q8
for (i = 0; i < inst->magnLen; i++) {
if (magn[i]) {
zeros = WebRtcSpl_NormU32((uint32_t)magn[i]);
frac = (int16_t)((((uint32_t)magn[i] << zeros)
& 0x7FFFFFFF) >> 23);
// log2(magn(i))
assert(frac < 256);
log2 = (int16_t)(((31 - zeros) << 8)
+ WebRtcNsx_kLogTableFrac[frac]);
// log2(magn(i))*log(2)
lmagn[i] = (int16_t)((log2 * log2_const) >> 15);
// + log(2^stages)
lmagn[i] += logval;
} else {
lmagn[i] = logval;//0;
}
}
// loop over simultaneous estimates
for (s = 0; s < SIMULT; s++) {
offset = s * inst->magnLen;
// Get counter values from state
counter = inst->noiseEstCounter[s];
assert(counter < 201);
countDiv = WebRtcNsx_kCounterDiv[counter];
countProd = (int16_t)(counter * countDiv);
// quant_est(...)
for (i = 0; i < inst->magnLen; i++) {
// compute delta
if (inst->noiseEstDensity[offset + i] > 512) {
// Get the value for delta by shifting intead of dividing.
int factor = WebRtcSpl_NormW16(inst->noiseEstDensity[offset + i]);
delta = (int16_t)(FACTOR_Q16 >> (14 - factor));
} else {
delta = FACTOR_Q7;
if (inst->blockIndex < END_STARTUP_LONG) {
// Smaller step size during startup. This prevents from using
// unrealistic values causing overflow.
delta = FACTOR_Q7_STARTUP;
}
}
// update log quantile estimate
tmp16 = (int16_t)((delta * countDiv) >> 14);
if (lmagn[i] > inst->noiseEstLogQuantile[offset + i]) {
// +=QUANTILE*delta/(inst->counter[s]+1) QUANTILE=0.25, =1 in Q2
// CounterDiv=1/(inst->counter[s]+1) in Q15
tmp16 += 2;
inst->noiseEstLogQuantile[offset + i] += tmp16 / 4;
} else {
tmp16 += 1;
// *(1-QUANTILE), in Q2 QUANTILE=0.25, 1-0.25=0.75=3 in Q2
// TODO(bjornv): investigate why we need to truncate twice.
tmp16no2 = (int16_t)((tmp16 / 2) * 3 / 2);
inst->noiseEstLogQuantile[offset + i] -= tmp16no2;
if (inst->noiseEstLogQuantile[offset + i] < logval) {
// This is the smallest fixed point representation we can
// have, hence we limit the output.
inst->noiseEstLogQuantile[offset + i] = logval;
}
}
// update density estimate
if (WEBRTC_SPL_ABS_W16(lmagn[i] - inst->noiseEstLogQuantile[offset + i])
< WIDTH_Q8) {
tmp16no1 = (int16_t)WEBRTC_SPL_MUL_16_16_RSFT_WITH_ROUND(
inst->noiseEstDensity[offset + i], countProd, 15);
tmp16no2 = (int16_t)WEBRTC_SPL_MUL_16_16_RSFT_WITH_ROUND(
width_factor, countDiv, 15);
inst->noiseEstDensity[offset + i] = tmp16no1 + tmp16no2;
}
} // end loop over magnitude spectrum
if (counter >= END_STARTUP_LONG) {
inst->noiseEstCounter[s] = 0;
if (inst->blockIndex >= END_STARTUP_LONG) {
UpdateNoiseEstimate(inst, offset);
}
}
inst->noiseEstCounter[s]++;
} // end loop over simultaneous estimates
// Sequentially update the noise during startup
if (inst->blockIndex < END_STARTUP_LONG) {
UpdateNoiseEstimate(inst, offset);
}
for (i = 0; i < inst->magnLen; i++) {
noise[i] = (uint32_t)(inst->noiseEstQuantile[i]); // Q(qNoise)
}
(*q_noise) = (int16_t)inst->qNoise;
}
// Filter the data in the frequency domain, and create spectrum.
static void PrepareSpectrumC(NoiseSuppressionFixedC* inst, int16_t* freq_buf) {
int i = 0, j = 0;
for (i = 0; i < inst->magnLen; i++) {
inst->real[i] = (int16_t)((inst->real[i] *
(int16_t)(inst->noiseSupFilter[i])) >> 14); // Q(normData-stages)
inst->imag[i] = (int16_t)((inst->imag[i] *
(int16_t)(inst->noiseSupFilter[i])) >> 14); // Q(normData-stages)
}
freq_buf[0] = inst->real[0];
freq_buf[1] = -inst->imag[0];
for (i = 1, j = 2; i < inst->anaLen2; i += 1, j += 2) {
freq_buf[j] = inst->real[i];
freq_buf[j + 1] = -inst->imag[i];
}
freq_buf[inst->anaLen] = inst->real[inst->anaLen2];
freq_buf[inst->anaLen + 1] = -inst->imag[inst->anaLen2];
}
// Denormalize the real-valued signal |in|, the output from inverse FFT.
static void DenormalizeC(NoiseSuppressionFixedC* inst,
int16_t* in,
int factor) {
int i = 0;
int32_t tmp32 = 0;
for (i = 0; i < inst->anaLen; i += 1) {
tmp32 = WEBRTC_SPL_SHIFT_W32((int32_t)in[i],
factor - inst->normData);
inst->real[i] = WebRtcSpl_SatW32ToW16(tmp32); // Q0
}
}
// For the noise supression process, synthesis, read out fully processed
// segment, and update synthesis buffer.
static void SynthesisUpdateC(NoiseSuppressionFixedC* inst,
int16_t* out_frame,
int16_t gain_factor) {
int i = 0;
int16_t tmp16a = 0;
int16_t tmp16b = 0;
int32_t tmp32 = 0;
// synthesis
for (i = 0; i < inst->anaLen; i++) {
tmp16a = (int16_t)WEBRTC_SPL_MUL_16_16_RSFT_WITH_ROUND(
inst->window[i], inst->real[i], 14); // Q0, window in Q14
tmp32 = WEBRTC_SPL_MUL_16_16_RSFT_WITH_ROUND(tmp16a, gain_factor, 13); // Q0
// Down shift with rounding
tmp16b = WebRtcSpl_SatW32ToW16(tmp32); // Q0
inst->synthesisBuffer[i] = WebRtcSpl_AddSatW16(inst->synthesisBuffer[i],
tmp16b); // Q0
}
// read out fully processed segment
for (i = 0; i < inst->blockLen10ms; i++) {
out_frame[i] = inst->synthesisBuffer[i]; // Q0
}
// update synthesis buffer
memcpy(inst->synthesisBuffer, inst->synthesisBuffer + inst->blockLen10ms,
(inst->anaLen - inst->blockLen10ms) * sizeof(*inst->synthesisBuffer));
WebRtcSpl_ZerosArrayW16(inst->synthesisBuffer
+ inst->anaLen - inst->blockLen10ms, inst->blockLen10ms);
}
// Update analysis buffer for lower band, and window data before FFT.
static void AnalysisUpdateC(NoiseSuppressionFixedC* inst,
int16_t* out,
int16_t* new_speech) {
int i = 0;
// For lower band update analysis buffer.
memcpy(inst->analysisBuffer, inst->analysisBuffer + inst->blockLen10ms,
(inst->anaLen - inst->blockLen10ms) * sizeof(*inst->analysisBuffer));
memcpy(inst->analysisBuffer + inst->anaLen - inst->blockLen10ms, new_speech,
inst->blockLen10ms * sizeof(*inst->analysisBuffer));
// Window data before FFT.
for (i = 0; i < inst->anaLen; i++) {
out[i] = (int16_t)WEBRTC_SPL_MUL_16_16_RSFT_WITH_ROUND(
inst->window[i], inst->analysisBuffer[i], 14); // Q0
}
}
// Normalize the real-valued signal |in|, the input to forward FFT.
static void NormalizeRealBufferC(NoiseSuppressionFixedC* inst,
const int16_t* in,
int16_t* out) {
int i = 0;
assert(inst->normData >= 0);
for (i = 0; i < inst->anaLen; ++i) {
out[i] = in[i] << inst->normData; // Q(normData)
}
}
// Declare function pointers.
NoiseEstimation WebRtcNsx_NoiseEstimation;
PrepareSpectrum WebRtcNsx_PrepareSpectrum;
SynthesisUpdate WebRtcNsx_SynthesisUpdate;
AnalysisUpdate WebRtcNsx_AnalysisUpdate;
Denormalize WebRtcNsx_Denormalize;
NormalizeRealBuffer WebRtcNsx_NormalizeRealBuffer;
#if (defined WEBRTC_DETECT_NEON || defined WEBRTC_HAS_NEON)
// Initialize function pointers for ARM Neon platform.
static void WebRtcNsx_InitNeon(void) {
WebRtcNsx_NoiseEstimation = WebRtcNsx_NoiseEstimationNeon;
WebRtcNsx_PrepareSpectrum = WebRtcNsx_PrepareSpectrumNeon;
WebRtcNsx_SynthesisUpdate = WebRtcNsx_SynthesisUpdateNeon;
WebRtcNsx_AnalysisUpdate = WebRtcNsx_AnalysisUpdateNeon;
}
#endif
#if defined(MIPS32_LE)
// Initialize function pointers for MIPS platform.
static void WebRtcNsx_InitMips(void) {
WebRtcNsx_PrepareSpectrum = WebRtcNsx_PrepareSpectrum_mips;
WebRtcNsx_SynthesisUpdate = WebRtcNsx_SynthesisUpdate_mips;
WebRtcNsx_AnalysisUpdate = WebRtcNsx_AnalysisUpdate_mips;
WebRtcNsx_NormalizeRealBuffer = WebRtcNsx_NormalizeRealBuffer_mips;
#if defined(MIPS_DSP_R1_LE)
WebRtcNsx_Denormalize = WebRtcNsx_Denormalize_mips;
#endif
}
#endif
void WebRtcNsx_CalcParametricNoiseEstimate(NoiseSuppressionFixedC* inst,
int16_t pink_noise_exp_avg,
int32_t pink_noise_num_avg,
int freq_index,
uint32_t* noise_estimate,
uint32_t* noise_estimate_avg) {
int32_t tmp32no1 = 0;
int32_t tmp32no2 = 0;
int16_t int_part = 0;
int16_t frac_part = 0;
// Use pink noise estimate
// noise_estimate = 2^(pinkNoiseNumerator + pinkNoiseExp * log2(j))
assert(freq_index >= 0);
assert(freq_index < 129);
tmp32no2 = (pink_noise_exp_avg * kLogIndex[freq_index]) >> 15; // Q11
tmp32no1 = pink_noise_num_avg - tmp32no2; // Q11
// Calculate output: 2^tmp32no1
// Output in Q(minNorm-stages)
tmp32no1 += (inst->minNorm - inst->stages) << 11;
if (tmp32no1 > 0) {
int_part = (int16_t)(tmp32no1 >> 11);
frac_part = (int16_t)(tmp32no1 & 0x000007ff); // Q11
// Piecewise linear approximation of 'b' in
// 2^(int_part+frac_part) = 2^int_part * (1 + b)
// 'b' is given in Q11 and below stored in frac_part.
if (frac_part >> 10) {
// Upper fractional part
tmp32no2 = (2048 - frac_part) * 1244; // Q21
tmp32no2 = 2048 - (tmp32no2 >> 10);
} else {
// Lower fractional part
tmp32no2 = (frac_part * 804) >> 10;
}
// Shift fractional part to Q(minNorm-stages)
tmp32no2 = WEBRTC_SPL_SHIFT_W32(tmp32no2, int_part - 11);
*noise_estimate_avg = (1 << int_part) + (uint32_t)tmp32no2;
// Scale up to initMagnEst, which is not block averaged
*noise_estimate = (*noise_estimate_avg) * (uint32_t)(inst->blockIndex + 1);
}
}
// Initialize state
int32_t WebRtcNsx_InitCore(NoiseSuppressionFixedC* inst, uint32_t fs) {
int i;
//check for valid pointer
if (inst == NULL) {
return -1;
}
//
// Initialization of struct
if (fs == 8000 || fs == 16000 || fs == 32000 || fs == 48000) {
inst->fs = fs;
} else {
return -1;
}
if (fs == 8000) {
inst->blockLen10ms = 80;
inst->anaLen = 128;
inst->stages = 7;
inst->window = kBlocks80w128x;
inst->thresholdLogLrt = 131072; //default threshold for LRT feature
inst->maxLrt = 0x0040000;
inst->minLrt = 52429;
} else {
inst->blockLen10ms = 160;
inst->anaLen = 256;
inst->stages = 8;
inst->window = kBlocks160w256x;
inst->thresholdLogLrt = 212644; //default threshold for LRT feature
inst->maxLrt = 0x0080000;
inst->minLrt = 104858;
}
inst->anaLen2 = inst->anaLen / 2;
inst->magnLen = inst->anaLen2 + 1;
if (inst->real_fft != NULL) {
WebRtcSpl_FreeRealFFT(inst->real_fft);
}
inst->real_fft = WebRtcSpl_CreateRealFFT(inst->stages);
if (inst->real_fft == NULL) {
return -1;
}
WebRtcSpl_ZerosArrayW16(inst->analysisBuffer, ANAL_BLOCKL_MAX);
WebRtcSpl_ZerosArrayW16(inst->synthesisBuffer, ANAL_BLOCKL_MAX);
// for HB processing
WebRtcSpl_ZerosArrayW16(inst->dataBufHBFX[0],
NUM_HIGH_BANDS_MAX * ANAL_BLOCKL_MAX);
// for quantile noise estimation
WebRtcSpl_ZerosArrayW16(inst->noiseEstQuantile, HALF_ANAL_BLOCKL);
for (i = 0; i < SIMULT * HALF_ANAL_BLOCKL; i++) {
inst->noiseEstLogQuantile[i] = 2048; // Q8
inst->noiseEstDensity[i] = 153; // Q9
}
for (i = 0; i < SIMULT; i++) {
inst->noiseEstCounter[i] = (int16_t)(END_STARTUP_LONG * (i + 1)) / SIMULT;
}
// Initialize suppression filter with ones
WebRtcSpl_MemSetW16((int16_t*)inst->noiseSupFilter, 16384, HALF_ANAL_BLOCKL);
// Set the aggressiveness: default
inst->aggrMode = 0;
//initialize variables for new method
inst->priorNonSpeechProb = 8192; // Q14(0.5) prior probability for speech/noise
for (i = 0; i < HALF_ANAL_BLOCKL; i++) {
inst->prevMagnU16[i] = 0;
inst->prevNoiseU32[i] = 0; //previous noise-spectrum
inst->logLrtTimeAvgW32[i] = 0; //smooth LR ratio
inst->avgMagnPause[i] = 0; //conservative noise spectrum estimate
inst->initMagnEst[i] = 0; //initial average magnitude spectrum
}
//feature quantities
inst->thresholdSpecDiff = 50; //threshold for difference feature: determined on-line
inst->thresholdSpecFlat = 20480; //threshold for flatness: determined on-line
inst->featureLogLrt = inst->thresholdLogLrt; //average LRT factor (= threshold)
inst->featureSpecFlat = inst->thresholdSpecFlat; //spectral flatness (= threshold)
inst->featureSpecDiff = inst->thresholdSpecDiff; //spectral difference (= threshold)
inst->weightLogLrt = 6; //default weighting par for LRT feature
inst->weightSpecFlat = 0; //default weighting par for spectral flatness feature
inst->weightSpecDiff = 0; //default weighting par for spectral difference feature
inst->curAvgMagnEnergy = 0; //window time-average of input magnitude spectrum
inst->timeAvgMagnEnergy = 0; //normalization for spectral difference
inst->timeAvgMagnEnergyTmp = 0; //normalization for spectral difference
//histogram quantities: used to estimate/update thresholds for features
WebRtcSpl_ZerosArrayW16(inst->histLrt, HIST_PAR_EST);
WebRtcSpl_ZerosArrayW16(inst->histSpecDiff, HIST_PAR_EST);
WebRtcSpl_ZerosArrayW16(inst->histSpecFlat, HIST_PAR_EST);
inst->blockIndex = -1; //frame counter
//inst->modelUpdate = 500; //window for update
inst->modelUpdate = (1 << STAT_UPDATES); //window for update
inst->cntThresUpdate = 0; //counter feature thresholds updates
inst->sumMagn = 0;
inst->magnEnergy = 0;
inst->prevQMagn = 0;
inst->qNoise = 0;
inst->prevQNoise = 0;
inst->energyIn = 0;
inst->scaleEnergyIn = 0;
inst->whiteNoiseLevel = 0;
inst->pinkNoiseNumerator = 0;
inst->pinkNoiseExp = 0;
inst->minNorm = 15; // Start with full scale
inst->zeroInputSignal = 0;
//default mode
WebRtcNsx_set_policy_core(inst, 0);
#ifdef NS_FILEDEBUG
inst->infile = fopen("indebug.pcm", "wb");
inst->outfile = fopen("outdebug.pcm", "wb");
inst->file1 = fopen("file1.pcm", "wb");
inst->file2 = fopen("file2.pcm", "wb");
inst->file3 = fopen("file3.pcm", "wb");
inst->file4 = fopen("file4.pcm", "wb");
inst->file5 = fopen("file5.pcm", "wb");
#endif
// Initialize function pointers.
WebRtcNsx_NoiseEstimation = NoiseEstimationC;
WebRtcNsx_PrepareSpectrum = PrepareSpectrumC;
WebRtcNsx_SynthesisUpdate = SynthesisUpdateC;
WebRtcNsx_AnalysisUpdate = AnalysisUpdateC;
WebRtcNsx_Denormalize = DenormalizeC;
WebRtcNsx_NormalizeRealBuffer = NormalizeRealBufferC;
#ifdef WEBRTC_DETECT_NEON
uint64_t features = WebRtc_GetCPUFeaturesARM();
if ((features & kCPUFeatureNEON) != 0) {
WebRtcNsx_InitNeon();
}
#elif defined(WEBRTC_HAS_NEON)
WebRtcNsx_InitNeon();
#endif
#if defined(MIPS32_LE)
WebRtcNsx_InitMips();
#endif
inst->initFlag = 1;
return 0;
}
int WebRtcNsx_set_policy_core(NoiseSuppressionFixedC* inst, int mode) {
// allow for modes:0,1,2,3
if (mode < 0 || mode > 3) {
return -1;
}
inst->aggrMode = mode;
if (mode == 0) {
inst->overdrive = 256; // Q8(1.0)
inst->denoiseBound = 8192; // Q14(0.5)
inst->gainMap = 0; // No gain compensation
} else if (mode == 1) {
inst->overdrive = 256; // Q8(1.0)
inst->denoiseBound = 4096; // Q14(0.25)
inst->factor2Table = kFactor2Aggressiveness1;
inst->gainMap = 1;
} else if (mode == 2) {
inst->overdrive = 282; // ~= Q8(1.1)
inst->denoiseBound = 2048; // Q14(0.125)
inst->factor2Table = kFactor2Aggressiveness2;
inst->gainMap = 1;
} else if (mode == 3) {
inst->overdrive = 320; // Q8(1.25)
inst->denoiseBound = 1475; // ~= Q14(0.09)
inst->factor2Table = kFactor2Aggressiveness3;
inst->gainMap = 1;
}
return 0;
}
// Extract thresholds for feature parameters
// histograms are computed over some window_size (given by window_pars)
// thresholds and weights are extracted every window
// flag 0 means update histogram only, flag 1 means compute the thresholds/weights
// threshold and weights are returned in: inst->priorModelPars
void WebRtcNsx_FeatureParameterExtraction(NoiseSuppressionFixedC* inst,
int flag) {
uint32_t tmpU32;
uint32_t histIndex;
uint32_t posPeak1SpecFlatFX, posPeak2SpecFlatFX;
uint32_t posPeak1SpecDiffFX, posPeak2SpecDiffFX;
int32_t tmp32;
int32_t fluctLrtFX, thresFluctLrtFX;
int32_t avgHistLrtFX, avgSquareHistLrtFX, avgHistLrtComplFX;
int16_t j;
int16_t numHistLrt;
int i;
int useFeatureSpecFlat, useFeatureSpecDiff, featureSum;
int maxPeak1, maxPeak2;
int weightPeak1SpecFlat, weightPeak2SpecFlat;
int weightPeak1SpecDiff, weightPeak2SpecDiff;
//update histograms
if (!flag) {
// LRT
// Type casting to UWord32 is safe since negative values will not be wrapped to larger
// values than HIST_PAR_EST
histIndex = (uint32_t)(inst->featureLogLrt);
if (histIndex < HIST_PAR_EST) {
inst->histLrt[histIndex]++;
}
// Spectral flatness
// (inst->featureSpecFlat*20)>>10 = (inst->featureSpecFlat*5)>>8
histIndex = (inst->featureSpecFlat * 5) >> 8;
if (histIndex < HIST_PAR_EST) {
inst->histSpecFlat[histIndex]++;
}
// Spectral difference
histIndex = HIST_PAR_EST;
if (inst->timeAvgMagnEnergy > 0) {
// Guard against division by zero
// If timeAvgMagnEnergy == 0 we have no normalizing statistics and
// therefore can't update the histogram
histIndex = ((inst->featureSpecDiff * 5) >> inst->stages) /
inst->timeAvgMagnEnergy;
}
if (histIndex < HIST_PAR_EST) {
inst->histSpecDiff[histIndex]++;
}
}
// extract parameters for speech/noise probability
if (flag) {
useFeatureSpecDiff = 1;
//for LRT feature:
// compute the average over inst->featureExtractionParams.rangeAvgHistLrt
avgHistLrtFX = 0;
avgSquareHistLrtFX = 0;
numHistLrt = 0;
for (i = 0; i < BIN_SIZE_LRT; i++) {
j = (2 * i + 1);
tmp32 = inst->histLrt[i] * j;
avgHistLrtFX += tmp32;
numHistLrt += inst->histLrt[i];
avgSquareHistLrtFX += tmp32 * j;
}
avgHistLrtComplFX = avgHistLrtFX;
for (; i < HIST_PAR_EST; i++) {
j = (2 * i + 1);
tmp32 = inst->histLrt[i] * j;
avgHistLrtComplFX += tmp32;
avgSquareHistLrtFX += tmp32 * j;
}
fluctLrtFX = avgSquareHistLrtFX * numHistLrt -
avgHistLrtFX * avgHistLrtComplFX;
thresFluctLrtFX = THRES_FLUCT_LRT * numHistLrt;
// get threshold for LRT feature:
tmpU32 = (FACTOR_1_LRT_DIFF * (uint32_t)avgHistLrtFX);
if ((fluctLrtFX < thresFluctLrtFX) || (numHistLrt == 0) ||
(tmpU32 > (uint32_t)(100 * numHistLrt))) {
//very low fluctuation, so likely noise
inst->thresholdLogLrt = inst->maxLrt;
} else {
tmp32 = (int32_t)((tmpU32 << (9 + inst->stages)) / numHistLrt /
25);
// check if value is within min/max range
inst->thresholdLogLrt = WEBRTC_SPL_SAT(inst->maxLrt,
tmp32,
inst->minLrt);
}
if (fluctLrtFX < thresFluctLrtFX) {
// Do not use difference feature if fluctuation of LRT feature is very low:
// most likely just noise state
useFeatureSpecDiff = 0;
}
// for spectral flatness and spectral difference: compute the main peaks of histogram
maxPeak1 = 0;
maxPeak2 = 0;
posPeak1SpecFlatFX = 0;
posPeak2SpecFlatFX = 0;
weightPeak1SpecFlat = 0;
weightPeak2SpecFlat = 0;
// peaks for flatness
for (i = 0; i < HIST_PAR_EST; i++) {
if (inst->histSpecFlat[i] > maxPeak1) {
// Found new "first" peak
maxPeak2 = maxPeak1;
weightPeak2SpecFlat = weightPeak1SpecFlat;
posPeak2SpecFlatFX = posPeak1SpecFlatFX;
maxPeak1 = inst->histSpecFlat[i];
weightPeak1SpecFlat = inst->histSpecFlat[i];
posPeak1SpecFlatFX = (uint32_t)(2 * i + 1);
} else if (inst->histSpecFlat[i] > maxPeak2) {
// Found new "second" peak
maxPeak2 = inst->histSpecFlat[i];
weightPeak2SpecFlat = inst->histSpecFlat[i];
posPeak2SpecFlatFX = (uint32_t)(2 * i + 1);
}
}
// for spectral flatness feature
useFeatureSpecFlat = 1;
// merge the two peaks if they are close
if ((posPeak1SpecFlatFX - posPeak2SpecFlatFX < LIM_PEAK_SPACE_FLAT_DIFF)
&& (weightPeak2SpecFlat * LIM_PEAK_WEIGHT_FLAT_DIFF > weightPeak1SpecFlat)) {
weightPeak1SpecFlat += weightPeak2SpecFlat;
posPeak1SpecFlatFX = (posPeak1SpecFlatFX + posPeak2SpecFlatFX) >> 1;
}
//reject if weight of peaks is not large enough, or peak value too small
if (weightPeak1SpecFlat < THRES_WEIGHT_FLAT_DIFF || posPeak1SpecFlatFX
< THRES_PEAK_FLAT) {
useFeatureSpecFlat = 0;
} else { // if selected, get the threshold
// compute the threshold and check if value is within min/max range
inst->thresholdSpecFlat = WEBRTC_SPL_SAT(MAX_FLAT_Q10, FACTOR_2_FLAT_Q10
* posPeak1SpecFlatFX, MIN_FLAT_Q10); //Q10
}
// done with flatness feature
if (useFeatureSpecDiff) {
//compute two peaks for spectral difference
maxPeak1 = 0;
maxPeak2 = 0;
posPeak1SpecDiffFX = 0;
posPeak2SpecDiffFX = 0;
weightPeak1SpecDiff = 0;
weightPeak2SpecDiff = 0;
// peaks for spectral difference
for (i = 0; i < HIST_PAR_EST; i++) {
if (inst->histSpecDiff[i] > maxPeak1) {
// Found new "first" peak
maxPeak2 = maxPeak1;
weightPeak2SpecDiff = weightPeak1SpecDiff;
posPeak2SpecDiffFX = posPeak1SpecDiffFX;
maxPeak1 = inst->histSpecDiff[i];
weightPeak1SpecDiff = inst->histSpecDiff[i];
posPeak1SpecDiffFX = (uint32_t)(2 * i + 1);
} else if (inst->histSpecDiff[i] > maxPeak2) {
// Found new "second" peak
maxPeak2 = inst->histSpecDiff[i];
weightPeak2SpecDiff = inst->histSpecDiff[i];
posPeak2SpecDiffFX = (uint32_t)(2 * i + 1);
}
}
// merge the two peaks if they are close
if ((posPeak1SpecDiffFX - posPeak2SpecDiffFX < LIM_PEAK_SPACE_FLAT_DIFF)
&& (weightPeak2SpecDiff * LIM_PEAK_WEIGHT_FLAT_DIFF > weightPeak1SpecDiff)) {
weightPeak1SpecDiff += weightPeak2SpecDiff;
posPeak1SpecDiffFX = (posPeak1SpecDiffFX + posPeak2SpecDiffFX) >> 1;
}
// get the threshold value and check if value is within min/max range
inst->thresholdSpecDiff = WEBRTC_SPL_SAT(MAX_DIFF, FACTOR_1_LRT_DIFF
* posPeak1SpecDiffFX, MIN_DIFF); //5x bigger
//reject if weight of peaks is not large enough
if (weightPeak1SpecDiff < THRES_WEIGHT_FLAT_DIFF) {
useFeatureSpecDiff = 0;
}
// done with spectral difference feature
}
// select the weights between the features
// inst->priorModelPars[4] is weight for LRT: always selected
featureSum = 6 / (1 + useFeatureSpecFlat + useFeatureSpecDiff);
inst->weightLogLrt = featureSum;
inst->weightSpecFlat = useFeatureSpecFlat * featureSum;
inst->weightSpecDiff = useFeatureSpecDiff * featureSum;
// set histograms to zero for next update
WebRtcSpl_ZerosArrayW16(inst->histLrt, HIST_PAR_EST);
WebRtcSpl_ZerosArrayW16(inst->histSpecDiff, HIST_PAR_EST);
WebRtcSpl_ZerosArrayW16(inst->histSpecFlat, HIST_PAR_EST);
} // end of flag == 1
}
// Compute spectral flatness on input spectrum
// magn is the magnitude spectrum
// spectral flatness is returned in inst->featureSpecFlat
void WebRtcNsx_ComputeSpectralFlatness(NoiseSuppressionFixedC* inst,
uint16_t* magn) {
uint32_t tmpU32;
uint32_t avgSpectralFlatnessNum, avgSpectralFlatnessDen;
int32_t tmp32;
int32_t currentSpectralFlatness, logCurSpectralFlatness;
int16_t zeros, frac, intPart;
int i;
// for flatness
avgSpectralFlatnessNum = 0;
avgSpectralFlatnessDen = inst->sumMagn - (uint32_t)magn[0]; // Q(normData-stages)
// compute log of ratio of the geometric to arithmetic mean: check for log(0) case
// flatness = exp( sum(log(magn[i]))/N - log(sum(magn[i])/N) )
// = exp( sum(log(magn[i]))/N ) * N / sum(magn[i])
// = 2^( sum(log2(magn[i]))/N - (log2(sum(magn[i])) - log2(N)) ) [This is used]
for (i = 1; i < inst->magnLen; i++) {
// First bin is excluded from spectrum measures. Number of bins is now a power of 2
if (magn[i]) {
zeros = WebRtcSpl_NormU32((uint32_t)magn[i]);
frac = (int16_t)(((uint32_t)((uint32_t)(magn[i]) << zeros)
& 0x7FFFFFFF) >> 23);
// log2(magn(i))
assert(frac < 256);
tmpU32 = (uint32_t)(((31 - zeros) << 8)
+ WebRtcNsx_kLogTableFrac[frac]); // Q8
avgSpectralFlatnessNum += tmpU32; // Q8
} else {
//if at least one frequency component is zero, treat separately
tmpU32 = WEBRTC_SPL_UMUL_32_16(inst->featureSpecFlat, SPECT_FLAT_TAVG_Q14); // Q24
inst->featureSpecFlat -= tmpU32 >> 14; // Q10
return;
}
}
//ratio and inverse log: check for case of log(0)
zeros = WebRtcSpl_NormU32(avgSpectralFlatnessDen);
frac = (int16_t)(((avgSpectralFlatnessDen << zeros) & 0x7FFFFFFF) >> 23);
// log2(avgSpectralFlatnessDen)
assert(frac < 256);
tmp32 = (int32_t)(((31 - zeros) << 8) + WebRtcNsx_kLogTableFrac[frac]); // Q8
logCurSpectralFlatness = (int32_t)avgSpectralFlatnessNum;
logCurSpectralFlatness += ((int32_t)(inst->stages - 1) << (inst->stages + 7)); // Q(8+stages-1)
logCurSpectralFlatness -= (tmp32 << (inst->stages - 1));
logCurSpectralFlatness <<= (10 - inst->stages); // Q17
tmp32 = (int32_t)(0x00020000 | (WEBRTC_SPL_ABS_W32(logCurSpectralFlatness)
& 0x0001FFFF)); //Q17
intPart = 7 - (logCurSpectralFlatness >> 17); // Add 7 for output in Q10.
if (intPart > 0) {
currentSpectralFlatness = tmp32 >> intPart;
} else {
currentSpectralFlatness = tmp32 << -intPart;
}
//time average update of spectral flatness feature
tmp32 = currentSpectralFlatness - (int32_t)inst->featureSpecFlat; // Q10
tmp32 *= SPECT_FLAT_TAVG_Q14; // Q24
inst->featureSpecFlat += tmp32 >> 14; // Q10
// done with flatness feature
}
// Compute the difference measure between input spectrum and a template/learned noise spectrum
// magn_tmp is the input spectrum
// the reference/template spectrum is inst->magn_avg_pause[i]
// returns (normalized) spectral difference in inst->featureSpecDiff
void WebRtcNsx_ComputeSpectralDifference(NoiseSuppressionFixedC* inst,
uint16_t* magnIn) {
// This is to be calculated:
// avgDiffNormMagn = var(magnIn) - cov(magnIn, magnAvgPause)^2 / var(magnAvgPause)
uint32_t tmpU32no1, tmpU32no2;
uint32_t varMagnUFX, varPauseUFX, avgDiffNormMagnUFX;
int32_t tmp32no1, tmp32no2;
int32_t avgPauseFX, avgMagnFX, covMagnPauseFX;
int32_t maxPause, minPause;
int16_t tmp16no1;
int i, norm32, nShifts;
avgPauseFX = 0;
maxPause = 0;
minPause = inst->avgMagnPause[0]; // Q(prevQMagn)
// compute average quantities
for (i = 0; i < inst->magnLen; i++) {
// Compute mean of magn_pause
avgPauseFX += inst->avgMagnPause[i]; // in Q(prevQMagn)
maxPause = WEBRTC_SPL_MAX(maxPause, inst->avgMagnPause[i]);
minPause = WEBRTC_SPL_MIN(minPause, inst->avgMagnPause[i]);
}
// normalize by replacing div of "inst->magnLen" with "inst->stages-1" shifts
avgPauseFX >>= inst->stages - 1;
avgMagnFX = inst->sumMagn >> (inst->stages - 1);
// Largest possible deviation in magnPause for (co)var calculations
tmp32no1 = WEBRTC_SPL_MAX(maxPause - avgPauseFX, avgPauseFX - minPause);
// Get number of shifts to make sure we don't get wrap around in varPause
nShifts = WEBRTC_SPL_MAX(0, 10 + inst->stages - WebRtcSpl_NormW32(tmp32no1));
varMagnUFX = 0;
varPauseUFX = 0;
covMagnPauseFX = 0;
for (i = 0; i < inst->magnLen; i++) {
// Compute var and cov of magn and magn_pause
tmp16no1 = (int16_t)((int32_t)magnIn[i] - avgMagnFX);
tmp32no2 = inst->avgMagnPause[i] - avgPauseFX;
varMagnUFX += (uint32_t)(tmp16no1 * tmp16no1); // Q(2*qMagn)
tmp32no1 = tmp32no2 * tmp16no1; // Q(prevQMagn+qMagn)
covMagnPauseFX += tmp32no1; // Q(prevQMagn+qMagn)
tmp32no1 = tmp32no2 >> nShifts; // Q(prevQMagn-minPause).
varPauseUFX += tmp32no1 * tmp32no1; // Q(2*(prevQMagn-minPause))
}
//update of average magnitude spectrum: Q(-2*stages) and averaging replaced by shifts
inst->curAvgMagnEnergy +=
inst->magnEnergy >> (2 * inst->normData + inst->stages - 1);
avgDiffNormMagnUFX = varMagnUFX; // Q(2*qMagn)
if ((varPauseUFX) && (covMagnPauseFX)) {
tmpU32no1 = (uint32_t)WEBRTC_SPL_ABS_W32(covMagnPauseFX); // Q(prevQMagn+qMagn)
norm32 = WebRtcSpl_NormU32(tmpU32no1) - 16;
if (norm32 > 0) {
tmpU32no1 <<= norm32; // Q(prevQMagn+qMagn+norm32)
} else {
tmpU32no1 >>= -norm32; // Q(prevQMagn+qMagn+norm32)
}
tmpU32no2 = WEBRTC_SPL_UMUL(tmpU32no1, tmpU32no1); // Q(2*(prevQMagn+qMagn-norm32))
nShifts += norm32;
nShifts <<= 1;
if (nShifts < 0) {
varPauseUFX >>= (-nShifts); // Q(2*(qMagn+norm32+minPause))
nShifts = 0;
}
if (varPauseUFX > 0) {
// Q(2*(qMagn+norm32-16+minPause))
tmpU32no1 = tmpU32no2 / varPauseUFX;
tmpU32no1 >>= nShifts;
// Q(2*qMagn)
avgDiffNormMagnUFX -= WEBRTC_SPL_MIN(avgDiffNormMagnUFX, tmpU32no1);
} else {
avgDiffNormMagnUFX = 0;
}
}
//normalize and compute time average update of difference feature
tmpU32no1 = avgDiffNormMagnUFX >> (2 * inst->normData);
if (inst->featureSpecDiff > tmpU32no1) {
tmpU32no2 = WEBRTC_SPL_UMUL_32_16(inst->featureSpecDiff - tmpU32no1,
SPECT_DIFF_TAVG_Q8); // Q(8-2*stages)
inst->featureSpecDiff -= tmpU32no2 >> 8; // Q(-2*stages)
} else {
tmpU32no2 = WEBRTC_SPL_UMUL_32_16(tmpU32no1 - inst->featureSpecDiff,
SPECT_DIFF_TAVG_Q8); // Q(8-2*stages)
inst->featureSpecDiff += tmpU32no2 >> 8; // Q(-2*stages)
}
}
// Transform input (speechFrame) to frequency domain magnitude (magnU16)
void WebRtcNsx_DataAnalysis(NoiseSuppressionFixedC* inst,
short* speechFrame,
uint16_t* magnU16) {
uint32_t tmpU32no1;
int32_t tmp_1_w32 = 0;
int32_t tmp_2_w32 = 0;
int32_t sum_log_magn = 0;
int32_t sum_log_i_log_magn = 0;
uint16_t sum_log_magn_u16 = 0;
uint16_t tmp_u16 = 0;
int16_t sum_log_i = 0;
int16_t sum_log_i_square = 0;
int16_t frac = 0;
int16_t log2 = 0;
int16_t matrix_determinant = 0;
int16_t maxWinData;
int i, j;
int zeros;
int net_norm = 0;
int right_shifts_in_magnU16 = 0;
int right_shifts_in_initMagnEst = 0;
int16_t winData_buff[ANAL_BLOCKL_MAX * 2 + 16];
int16_t realImag_buff[ANAL_BLOCKL_MAX * 2 + 16];
// Align the structures to 32-byte boundary for the FFT function.
int16_t* winData = (int16_t*) (((uintptr_t)winData_buff + 31) & ~31);
int16_t* realImag = (int16_t*) (((uintptr_t) realImag_buff + 31) & ~31);
// Update analysis buffer for lower band, and window data before FFT.
WebRtcNsx_AnalysisUpdate(inst, winData, speechFrame);
// Get input energy
inst->energyIn =
WebRtcSpl_Energy(winData, inst->anaLen, &inst->scaleEnergyIn);
// Reset zero input flag
inst->zeroInputSignal = 0;
// Acquire norm for winData
maxWinData = WebRtcSpl_MaxAbsValueW16(winData, inst->anaLen);
inst->normData = WebRtcSpl_NormW16(maxWinData);
if (maxWinData == 0) {
// Treat zero input separately.
inst->zeroInputSignal = 1;
return;
}
// Determine the net normalization in the frequency domain
net_norm = inst->stages - inst->normData;
// Track lowest normalization factor and use it to prevent wrap around in shifting
right_shifts_in_magnU16 = inst->normData - inst->minNorm;
right_shifts_in_initMagnEst = WEBRTC_SPL_MAX(-right_shifts_in_magnU16, 0);
inst->minNorm -= right_shifts_in_initMagnEst;
right_shifts_in_magnU16 = WEBRTC_SPL_MAX(right_shifts_in_magnU16, 0);
// create realImag as winData interleaved with zeros (= imag. part), normalize it
WebRtcNsx_NormalizeRealBuffer(inst, winData, realImag);
// FFT output will be in winData[].
WebRtcSpl_RealForwardFFT(inst->real_fft, realImag, winData);
inst->imag[0] = 0; // Q(normData-stages)
inst->imag[inst->anaLen2] = 0;
inst->real[0] = winData[0]; // Q(normData-stages)
inst->real[inst->anaLen2] = winData[inst->anaLen];
// Q(2*(normData-stages))
inst->magnEnergy = (uint32_t)(inst->real[0] * inst->real[0]);
inst->magnEnergy += (uint32_t)(inst->real[inst->anaLen2] *
inst->real[inst->anaLen2]);
magnU16[0] = (uint16_t)WEBRTC_SPL_ABS_W16(inst->real[0]); // Q(normData-stages)
magnU16[inst->anaLen2] = (uint16_t)WEBRTC_SPL_ABS_W16(inst->real[inst->anaLen2]);
inst->sumMagn = (uint32_t)magnU16[0]; // Q(normData-stages)
inst->sumMagn += (uint32_t)magnU16[inst->anaLen2];
if (inst->blockIndex >= END_STARTUP_SHORT) {
for (i = 1, j = 2; i < inst->anaLen2; i += 1, j += 2) {
inst->real[i] = winData[j];
inst->imag[i] = -winData[j + 1];
// magnitude spectrum
// energy in Q(2*(normData-stages))
tmpU32no1 = (uint32_t)(winData[j] * winData[j]);
tmpU32no1 += (uint32_t)(winData[j + 1] * winData[j + 1]);
inst->magnEnergy += tmpU32no1; // Q(2*(normData-stages))
magnU16[i] = (uint16_t)WebRtcSpl_SqrtFloor(tmpU32no1); // Q(normData-stages)
inst->sumMagn += (uint32_t)magnU16[i]; // Q(normData-stages)
}
} else {
//
// Gather information during startup for noise parameter estimation
//
// Switch initMagnEst to Q(minNorm-stages)
inst->initMagnEst[0] >>= right_shifts_in_initMagnEst;
inst->initMagnEst[inst->anaLen2] >>= right_shifts_in_initMagnEst;
// Update initMagnEst with magnU16 in Q(minNorm-stages).
inst->initMagnEst[0] += magnU16[0] >> right_shifts_in_magnU16;
inst->initMagnEst[inst->anaLen2] +=
magnU16[inst->anaLen2] >> right_shifts_in_magnU16;
log2 = 0;
if (magnU16[inst->anaLen2]) {
// Calculate log2(magnU16[inst->anaLen2])
zeros = WebRtcSpl_NormU32((uint32_t)magnU16[inst->anaLen2]);
frac = (int16_t)((((uint32_t)magnU16[inst->anaLen2] << zeros) &
0x7FFFFFFF) >> 23); // Q8
// log2(magnU16(i)) in Q8
assert(frac < 256);
log2 = (int16_t)(((31 - zeros) << 8) + WebRtcNsx_kLogTableFrac[frac]);
}
sum_log_magn = (int32_t)log2; // Q8
// sum_log_i_log_magn in Q17
sum_log_i_log_magn = (kLogIndex[inst->anaLen2] * log2) >> 3;
for (i = 1, j = 2; i < inst->anaLen2; i += 1, j += 2) {
inst->real[i] = winData[j];
inst->imag[i] = -winData[j + 1];
// magnitude spectrum
// energy in Q(2*(normData-stages))
tmpU32no1 = (uint32_t)(winData[j] * winData[j]);
tmpU32no1 += (uint32_t)(winData[j + 1] * winData[j + 1]);
inst->magnEnergy += tmpU32no1; // Q(2*(normData-stages))
magnU16[i] = (uint16_t)WebRtcSpl_SqrtFloor(tmpU32no1); // Q(normData-stages)
inst->sumMagn += (uint32_t)magnU16[i]; // Q(normData-stages)
// Switch initMagnEst to Q(minNorm-stages)
inst->initMagnEst[i] >>= right_shifts_in_initMagnEst;
// Update initMagnEst with magnU16 in Q(minNorm-stages).
inst->initMagnEst[i] += magnU16[i] >> right_shifts_in_magnU16;
if (i >= kStartBand) {
// For pink noise estimation. Collect data neglecting lower frequency band
log2 = 0;
if (magnU16[i]) {
zeros = WebRtcSpl_NormU32((uint32_t)magnU16[i]);
frac = (int16_t)((((uint32_t)magnU16[i] << zeros) &
0x7FFFFFFF) >> 23);
// log2(magnU16(i)) in Q8
assert(frac < 256);
log2 = (int16_t)(((31 - zeros) << 8)
+ WebRtcNsx_kLogTableFrac[frac]);
}
sum_log_magn += (int32_t)log2; // Q8
// sum_log_i_log_magn in Q17
sum_log_i_log_magn += (kLogIndex[i] * log2) >> 3;
}
}
//
//compute simplified noise model during startup
//
// Estimate White noise
// Switch whiteNoiseLevel to Q(minNorm-stages)
inst->whiteNoiseLevel >>= right_shifts_in_initMagnEst;
// Update the average magnitude spectrum, used as noise estimate.
tmpU32no1 = WEBRTC_SPL_UMUL_32_16(inst->sumMagn, inst->overdrive);
tmpU32no1 >>= inst->stages + 8;
// Replacing division above with 'stages' shifts
// Shift to same Q-domain as whiteNoiseLevel
tmpU32no1 >>= right_shifts_in_magnU16;
// This operation is safe from wrap around as long as END_STARTUP_SHORT < 128
assert(END_STARTUP_SHORT < 128);
inst->whiteNoiseLevel += tmpU32no1; // Q(minNorm-stages)
// Estimate Pink noise parameters
// Denominator used in both parameter estimates.
// The value is only dependent on the size of the frequency band (kStartBand)
// and to reduce computational complexity stored in a table (kDeterminantEstMatrix[])
assert(kStartBand < 66);
matrix_determinant = kDeterminantEstMatrix[kStartBand]; // Q0
sum_log_i = kSumLogIndex[kStartBand]; // Q5
sum_log_i_square = kSumSquareLogIndex[kStartBand]; // Q2
if (inst->fs == 8000) {
// Adjust values to shorter blocks in narrow band.
tmp_1_w32 = (int32_t)matrix_determinant;
tmp_1_w32 += (kSumLogIndex[65] * sum_log_i) >> 9;
tmp_1_w32 -= (kSumLogIndex[65] * kSumLogIndex[65]) >> 10;
tmp_1_w32 -= (int32_t)sum_log_i_square << 4;
tmp_1_w32 -= ((inst->magnLen - kStartBand) * kSumSquareLogIndex[65]) >> 2;
matrix_determinant = (int16_t)tmp_1_w32;
sum_log_i -= kSumLogIndex[65]; // Q5
sum_log_i_square -= kSumSquareLogIndex[65]; // Q2
}
// Necessary number of shifts to fit sum_log_magn in a word16
zeros = 16 - WebRtcSpl_NormW32(sum_log_magn);
if (zeros < 0) {
zeros = 0;
}
tmp_1_w32 = sum_log_magn << 1; // Q9
sum_log_magn_u16 = (uint16_t)(tmp_1_w32 >> zeros); // Q(9-zeros).
// Calculate and update pinkNoiseNumerator. Result in Q11.
tmp_2_w32 = WEBRTC_SPL_MUL_16_U16(sum_log_i_square, sum_log_magn_u16); // Q(11-zeros)
tmpU32no1 = sum_log_i_log_magn >> 12; // Q5
// Shift the largest value of sum_log_i and tmp32no3 before multiplication
tmp_u16 = ((uint16_t)sum_log_i << 1); // Q6
if ((uint32_t)sum_log_i > tmpU32no1) {
tmp_u16 >>= zeros;
} else {
tmpU32no1 >>= zeros;
}
tmp_2_w32 -= (int32_t)WEBRTC_SPL_UMUL_32_16(tmpU32no1, tmp_u16); // Q(11-zeros)
matrix_determinant >>= zeros; // Q(-zeros)
tmp_2_w32 = WebRtcSpl_DivW32W16(tmp_2_w32, matrix_determinant); // Q11
tmp_2_w32 += (int32_t)net_norm << 11; // Q11
if (tmp_2_w32 < 0) {
tmp_2_w32 = 0;
}
inst->pinkNoiseNumerator += tmp_2_w32; // Q11
// Calculate and update pinkNoiseExp. Result in Q14.
tmp_2_w32 = WEBRTC_SPL_MUL_16_U16(sum_log_i, sum_log_magn_u16); // Q(14-zeros)
tmp_1_w32 = sum_log_i_log_magn >> (3 + zeros);
tmp_1_w32 *= inst->magnLen - kStartBand;
tmp_2_w32 -= tmp_1_w32; // Q(14-zeros)
if (tmp_2_w32 > 0) {
// If the exponential parameter is negative force it to zero, which means a
// flat spectrum.
tmp_1_w32 = WebRtcSpl_DivW32W16(tmp_2_w32, matrix_determinant); // Q14
inst->pinkNoiseExp += WEBRTC_SPL_SAT(16384, tmp_1_w32, 0); // Q14
}
}
}
void WebRtcNsx_DataSynthesis(NoiseSuppressionFixedC* inst, short* outFrame) {
int32_t energyOut;
int16_t realImag_buff[ANAL_BLOCKL_MAX * 2 + 16];
int16_t rfft_out_buff[ANAL_BLOCKL_MAX * 2 + 16];
// Align the structures to 32-byte boundary for the FFT function.
int16_t* realImag = (int16_t*) (((uintptr_t)realImag_buff + 31) & ~31);
int16_t* rfft_out = (int16_t*) (((uintptr_t) rfft_out_buff + 31) & ~31);
int16_t tmp16no1, tmp16no2;
int16_t energyRatio;
int16_t gainFactor, gainFactor1, gainFactor2;
int i;
int outCIFFT;
int scaleEnergyOut = 0;
if (inst->zeroInputSignal) {
// synthesize the special case of zero input
// read out fully processed segment
for (i = 0; i < inst->blockLen10ms; i++) {
outFrame[i] = inst->synthesisBuffer[i]; // Q0
}
// update synthesis buffer
memcpy(inst->synthesisBuffer, inst->synthesisBuffer + inst->blockLen10ms,
(inst->anaLen - inst->blockLen10ms) * sizeof(*inst->synthesisBuffer));
WebRtcSpl_ZerosArrayW16(inst->synthesisBuffer + inst->anaLen - inst->blockLen10ms,
inst->blockLen10ms);
return;
}
// Filter the data in the frequency domain, and create spectrum.
WebRtcNsx_PrepareSpectrum(inst, realImag);
// Inverse FFT output will be in rfft_out[].
outCIFFT = WebRtcSpl_RealInverseFFT(inst->real_fft, realImag, rfft_out);
WebRtcNsx_Denormalize(inst, rfft_out, outCIFFT);
//scale factor: only do it after END_STARTUP_LONG time
gainFactor = 8192; // 8192 = Q13(1.0)
if (inst->gainMap == 1 &&
inst->blockIndex > END_STARTUP_LONG &&
inst->energyIn > 0) {
// Q(-scaleEnergyOut)
energyOut = WebRtcSpl_Energy(inst->real, inst->anaLen, &scaleEnergyOut);
if (scaleEnergyOut == 0 && !(energyOut & 0x7f800000)) {
energyOut = WEBRTC_SPL_SHIFT_W32(energyOut, 8 + scaleEnergyOut
- inst->scaleEnergyIn);
} else {
// |energyIn| is currently in Q(|scaleEnergyIn|), but to later on end up
// with an |energyRatio| in Q8 we need to change the Q-domain to
// Q(-8-scaleEnergyOut).
inst->energyIn >>= 8 + scaleEnergyOut - inst->scaleEnergyIn;
}
assert(inst->energyIn > 0);
energyRatio = (energyOut + inst->energyIn / 2) / inst->energyIn; // Q8
// Limit the ratio to [0, 1] in Q8, i.e., [0, 256]
energyRatio = WEBRTC_SPL_SAT(256, energyRatio, 0);
// all done in lookup tables now
assert(energyRatio < 257);
gainFactor1 = kFactor1Table[energyRatio]; // Q8
gainFactor2 = inst->factor2Table[energyRatio]; // Q8
//combine both scales with speech/noise prob: note prior (priorSpeechProb) is not frequency dependent
// factor = inst->priorSpeechProb*factor1 + (1.0-inst->priorSpeechProb)*factor2; // original code
tmp16no1 = (int16_t)(((16384 - inst->priorNonSpeechProb) * gainFactor1) >>
14); // in Q13, where 16384 = Q14(1.0)
tmp16no2 = (int16_t)((inst->priorNonSpeechProb * gainFactor2) >> 14);
gainFactor = tmp16no1 + tmp16no2; // Q13
} // out of flag_gain_map==1
// Synthesis, read out fully processed segment, and update synthesis buffer.
WebRtcNsx_SynthesisUpdate(inst, outFrame, gainFactor);
}
void WebRtcNsx_ProcessCore(NoiseSuppressionFixedC* inst,
const short* const* speechFrame,
int num_bands,
short* const* outFrame) {
// main routine for noise suppression
uint32_t tmpU32no1, tmpU32no2, tmpU32no3;
uint32_t satMax, maxNoiseU32;
uint32_t tmpMagnU32, tmpNoiseU32;
uint32_t nearMagnEst;
uint32_t noiseUpdateU32;
uint32_t noiseU32[HALF_ANAL_BLOCKL];
uint32_t postLocSnr[HALF_ANAL_BLOCKL];
uint32_t priorLocSnr[HALF_ANAL_BLOCKL];
uint32_t prevNearSnr[HALF_ANAL_BLOCKL];
uint32_t curNearSnr;
uint32_t priorSnr;
uint32_t noise_estimate = 0;
uint32_t noise_estimate_avg = 0;
uint32_t numerator = 0;
int32_t tmp32no1, tmp32no2;
int32_t pink_noise_num_avg = 0;
uint16_t tmpU16no1;
uint16_t magnU16[HALF_ANAL_BLOCKL];
uint16_t prevNoiseU16[HALF_ANAL_BLOCKL];
uint16_t nonSpeechProbFinal[HALF_ANAL_BLOCKL];
uint16_t gammaNoise, prevGammaNoise;
uint16_t noiseSupFilterTmp[HALF_ANAL_BLOCKL];
int16_t qMagn, qNoise;
int16_t avgProbSpeechHB, gainModHB, avgFilterGainHB, gainTimeDomainHB;
int16_t pink_noise_exp_avg = 0;
int i, j;
int nShifts, postShifts;
int norm32no1, norm32no2;
int flag, sign;
int q_domain_to_use = 0;
// Code for ARMv7-Neon platform assumes the following:
assert(inst->anaLen > 0);
assert(inst->anaLen2 > 0);
assert(inst->anaLen % 16 == 0);
assert(inst->anaLen2 % 8 == 0);
assert(inst->blockLen10ms > 0);
assert(inst->blockLen10ms % 16 == 0);
assert(inst->magnLen == inst->anaLen2 + 1);
#ifdef NS_FILEDEBUG
if (fwrite(spframe, sizeof(short),
inst->blockLen10ms, inst->infile) != inst->blockLen10ms) {
assert(false);
}
#endif
// Check that initialization has been done
assert(inst->initFlag == 1);
assert((num_bands - 1) <= NUM_HIGH_BANDS_MAX);
const short* const* speechFrameHB = NULL;
short* const* outFrameHB = NULL;
int num_high_bands = 0;
if (num_bands > 1) {
speechFrameHB = &speechFrame[1];
outFrameHB = &outFrame[1];
num_high_bands = num_bands - 1;
}
// Store speechFrame and transform to frequency domain
WebRtcNsx_DataAnalysis(inst, (short*)speechFrame[0], magnU16);
if (inst->zeroInputSignal) {
WebRtcNsx_DataSynthesis(inst, outFrame[0]);
if (num_bands > 1) {
// update analysis buffer for H band
// append new data to buffer FX
for (i = 0; i < num_high_bands; ++i) {
int block_shift = inst->anaLen - inst->blockLen10ms;
memcpy(inst->dataBufHBFX[i], inst->dataBufHBFX[i] + inst->blockLen10ms,
block_shift * sizeof(*inst->dataBufHBFX[i]));
memcpy(inst->dataBufHBFX[i] + block_shift, speechFrameHB[i],
inst->blockLen10ms * sizeof(*inst->dataBufHBFX[i]));
for (j = 0; j < inst->blockLen10ms; j++) {
outFrameHB[i][j] = inst->dataBufHBFX[i][j]; // Q0
}
}
} // end of H band gain computation
return;
}
// Update block index when we have something to process
inst->blockIndex++;
//
// Norm of magn
qMagn = inst->normData - inst->stages;
// Compute spectral flatness on input spectrum
WebRtcNsx_ComputeSpectralFlatness(inst, magnU16);
// quantile noise estimate
WebRtcNsx_NoiseEstimation(inst, magnU16, noiseU32, &qNoise);
//noise estimate from previous frame
for (i = 0; i < inst->magnLen; i++) {
prevNoiseU16[i] = (uint16_t)(inst->prevNoiseU32[i] >> 11); // Q(prevQNoise)
}
if (inst->blockIndex < END_STARTUP_SHORT) {
// Noise Q-domain to be used later; see description at end of section.
q_domain_to_use = WEBRTC_SPL_MIN((int)qNoise, inst->minNorm - inst->stages);
// Calculate frequency independent parts in parametric noise estimate and calculate
// the estimate for the lower frequency band (same values for all frequency bins)
if (inst->pinkNoiseExp) {
pink_noise_exp_avg = (int16_t)WebRtcSpl_DivW32W16(inst->pinkNoiseExp,
(int16_t)(inst->blockIndex + 1)); // Q14
pink_noise_num_avg = WebRtcSpl_DivW32W16(inst->pinkNoiseNumerator,
(int16_t)(inst->blockIndex + 1)); // Q11
WebRtcNsx_CalcParametricNoiseEstimate(inst,
pink_noise_exp_avg,
pink_noise_num_avg,
kStartBand,
&noise_estimate,
&noise_estimate_avg);
} else {
// Use white noise estimate if we have poor pink noise parameter estimates
noise_estimate = inst->whiteNoiseLevel; // Q(minNorm-stages)
noise_estimate_avg = noise_estimate / (inst->blockIndex + 1); // Q(minNorm-stages)
}
for (i = 0; i < inst->magnLen; i++) {
// Estimate the background noise using the pink noise parameters if permitted
if ((inst->pinkNoiseExp) && (i >= kStartBand)) {
// Reset noise_estimate
noise_estimate = 0;
noise_estimate_avg = 0;
// Calculate the parametric noise estimate for current frequency bin
WebRtcNsx_CalcParametricNoiseEstimate(inst,
pink_noise_exp_avg,
pink_noise_num_avg,
i,
&noise_estimate,
&noise_estimate_avg);
}
// Calculate parametric Wiener filter
noiseSupFilterTmp[i] = inst->denoiseBound;
if (inst->initMagnEst[i]) {
// numerator = (initMagnEst - noise_estimate * overdrive)
// Result in Q(8+minNorm-stages)
tmpU32no1 = WEBRTC_SPL_UMUL_32_16(noise_estimate, inst->overdrive);
numerator = inst->initMagnEst[i] << 8;
if (numerator > tmpU32no1) {
// Suppression filter coefficient larger than zero, so calculate.
numerator -= tmpU32no1;
// Determine number of left shifts in numerator for best accuracy after
// division
nShifts = WebRtcSpl_NormU32(numerator);
nShifts = WEBRTC_SPL_SAT(6, nShifts, 0);
// Shift numerator to Q(nShifts+8+minNorm-stages)
numerator <<= nShifts;
// Shift denominator to Q(nShifts-6+minNorm-stages)
tmpU32no1 = inst->initMagnEst[i] >> (6 - nShifts);
if (tmpU32no1 == 0) {
// This is only possible if numerator = 0, in which case
// we don't need any division.
tmpU32no1 = 1;
}
tmpU32no2 = numerator / tmpU32no1; // Q14
noiseSupFilterTmp[i] = (uint16_t)WEBRTC_SPL_SAT(16384, tmpU32no2,
(uint32_t)(inst->denoiseBound)); // Q14
}
}
// Weight quantile noise 'noiseU32' with modeled noise 'noise_estimate_avg'
// 'noiseU32 is in Q(qNoise) and 'noise_estimate' in Q(minNorm-stages)
// To guarantee that we do not get wrap around when shifting to the same domain
// we use the lowest one. Furthermore, we need to save 6 bits for the weighting.
// 'noise_estimate_avg' can handle this operation by construction, but 'noiseU32'
// may not.
// Shift 'noiseU32' to 'q_domain_to_use'
tmpU32no1 = noiseU32[i] >> (qNoise - q_domain_to_use);
// Shift 'noise_estimate_avg' to 'q_domain_to_use'
tmpU32no2 = noise_estimate_avg >>
(inst->minNorm - inst->stages - q_domain_to_use);
// Make a simple check to see if we have enough room for weighting 'tmpU32no1'
// without wrap around
nShifts = 0;
if (tmpU32no1 & 0xfc000000) {
tmpU32no1 >>= 6;
tmpU32no2 >>= 6;
nShifts = 6;
}
tmpU32no1 *= inst->blockIndex;
tmpU32no2 *= (END_STARTUP_SHORT - inst->blockIndex);
// Add them together and divide by startup length
noiseU32[i] = WebRtcSpl_DivU32U16(tmpU32no1 + tmpU32no2, END_STARTUP_SHORT);
// Shift back if necessary
noiseU32[i] <<= nShifts;
}
// Update new Q-domain for 'noiseU32'
qNoise = q_domain_to_use;
}
// compute average signal during END_STARTUP_LONG time:
// used to normalize spectral difference measure
if (inst->blockIndex < END_STARTUP_LONG) {
// substituting division with shift ending up in Q(-2*stages)
inst->timeAvgMagnEnergyTmp +=
inst->magnEnergy >> (2 * inst->normData + inst->stages - 1);
inst->timeAvgMagnEnergy = WebRtcSpl_DivU32U16(inst->timeAvgMagnEnergyTmp,
inst->blockIndex + 1);
}
//start processing at frames == converged+1
// STEP 1: compute prior and post SNR based on quantile noise estimates
// compute direct decision (DD) estimate of prior SNR: needed for new method
satMax = (uint32_t)1048575;// Largest possible value without getting overflow despite shifting 12 steps
postShifts = 6 + qMagn - qNoise;
nShifts = 5 - inst->prevQMagn + inst->prevQNoise;
for (i = 0; i < inst->magnLen; i++) {
// FLOAT:
// post SNR
// postLocSnr[i] = 0.0;
// if (magn[i] > noise[i])
// {
// postLocSnr[i] = magn[i] / (noise[i] + 0.0001);
// }
// // previous post SNR
// // previous estimate: based on previous frame with gain filter (smooth is previous filter)
//
// prevNearSnr[i] = inst->prevMagnU16[i] / (inst->noisePrev[i] + 0.0001) * (inst->smooth[i]);
//
// // DD estimate is sum of two terms: current estimate and previous estimate
// // directed decision update of priorSnr (or we actually store [2*priorSnr+1])
//
// priorLocSnr[i] = DD_PR_SNR * prevNearSnr[i] + (1.0 - DD_PR_SNR) * (postLocSnr[i] - 1.0);
// calculate post SNR: output in Q11
postLocSnr[i] = 2048; // 1.0 in Q11
tmpU32no1 = (uint32_t)magnU16[i] << 6; // Q(6+qMagn)
if (postShifts < 0) {
tmpU32no2 = noiseU32[i] >> -postShifts; // Q(6+qMagn)
} else {
tmpU32no2 = noiseU32[i] << postShifts; // Q(6+qMagn)
}
if (tmpU32no1 > tmpU32no2) {
// Current magnitude larger than noise
tmpU32no1 <<= 11; // Q(17+qMagn)
if (tmpU32no2 > 0) {
tmpU32no1 /= tmpU32no2; // Q11
postLocSnr[i] = WEBRTC_SPL_MIN(satMax, tmpU32no1); // Q11
} else {
postLocSnr[i] = satMax;
}
}
// calculate prevNearSnr[i] and save for later instead of recalculating it later
// |nearMagnEst| in Q(prevQMagn + 14)
nearMagnEst = inst->prevMagnU16[i] * inst->noiseSupFilter[i];
tmpU32no1 = nearMagnEst << 3; // Q(prevQMagn+17)
tmpU32no2 = inst->prevNoiseU32[i] >> nShifts; // Q(prevQMagn+6)
if (tmpU32no2 > 0) {
tmpU32no1 /= tmpU32no2; // Q11
tmpU32no1 = WEBRTC_SPL_MIN(satMax, tmpU32no1); // Q11
} else {
tmpU32no1 = satMax; // Q11
}
prevNearSnr[i] = tmpU32no1; // Q11
//directed decision update of priorSnr
tmpU32no1 = WEBRTC_SPL_UMUL_32_16(prevNearSnr[i], DD_PR_SNR_Q11); // Q22
tmpU32no2 = WEBRTC_SPL_UMUL_32_16(postLocSnr[i] - 2048, ONE_MINUS_DD_PR_SNR_Q11); // Q22
priorSnr = tmpU32no1 + tmpU32no2 + 512; // Q22 (added 512 for rounding)
// priorLocSnr = 1 + 2*priorSnr
priorLocSnr[i] = 2048 + (priorSnr >> 10); // Q11
} // end of loop over frequencies
// done with step 1: DD computation of prior and post SNR
// STEP 2: compute speech/noise likelihood
//compute difference of input spectrum with learned/estimated noise spectrum
WebRtcNsx_ComputeSpectralDifference(inst, magnU16);
//compute histograms for determination of parameters (thresholds and weights for features)
//parameters are extracted once every window time (=inst->modelUpdate)
//counter update
inst->cntThresUpdate++;
flag = (int)(inst->cntThresUpdate == inst->modelUpdate);
//update histogram
WebRtcNsx_FeatureParameterExtraction(inst, flag);
//compute model parameters
if (flag) {
inst->cntThresUpdate = 0; // Reset counter
//update every window:
// get normalization for spectral difference for next window estimate
// Shift to Q(-2*stages)
inst->curAvgMagnEnergy >>= STAT_UPDATES;
tmpU32no1 = (inst->curAvgMagnEnergy + inst->timeAvgMagnEnergy + 1) >> 1; //Q(-2*stages)
// Update featureSpecDiff
if ((tmpU32no1 != inst->timeAvgMagnEnergy) && (inst->featureSpecDiff) &&
(inst->timeAvgMagnEnergy > 0)) {
norm32no1 = 0;
tmpU32no3 = tmpU32no1;
while (0xFFFF0000 & tmpU32no3) {
tmpU32no3 >>= 1;
norm32no1++;
}
tmpU32no2 = inst->featureSpecDiff;
while (0xFFFF0000 & tmpU32no2) {
tmpU32no2 >>= 1;
norm32no1++;
}
tmpU32no3 = WEBRTC_SPL_UMUL(tmpU32no3, tmpU32no2);
tmpU32no3 /= inst->timeAvgMagnEnergy;
if (WebRtcSpl_NormU32(tmpU32no3) < norm32no1) {
inst->featureSpecDiff = 0x007FFFFF;
} else {
inst->featureSpecDiff = WEBRTC_SPL_MIN(0x007FFFFF,
tmpU32no3 << norm32no1);
}
}
inst->timeAvgMagnEnergy = tmpU32no1; // Q(-2*stages)
inst->curAvgMagnEnergy = 0;
}
//compute speech/noise probability
WebRtcNsx_SpeechNoiseProb(inst, nonSpeechProbFinal, priorLocSnr, postLocSnr);
//time-avg parameter for noise update
gammaNoise = NOISE_UPDATE_Q8; // Q8
maxNoiseU32 = 0;
postShifts = inst->prevQNoise - qMagn;
nShifts = inst->prevQMagn - qMagn;
for (i = 0; i < inst->magnLen; i++) {
// temporary noise update: use it for speech frames if update value is less than previous
// the formula has been rewritten into:
// noiseUpdate = noisePrev[i] + (1 - gammaNoise) * nonSpeechProb * (magn[i] - noisePrev[i])
if (postShifts < 0) {
tmpU32no2 = magnU16[i] >> -postShifts; // Q(prevQNoise)
} else {
tmpU32no2 = (uint32_t)magnU16[i] << postShifts; // Q(prevQNoise)
}
if (prevNoiseU16[i] > tmpU32no2) {
sign = -1;
tmpU32no1 = prevNoiseU16[i] - tmpU32no2;
} else {
sign = 1;
tmpU32no1 = tmpU32no2 - prevNoiseU16[i];
}
noiseUpdateU32 = inst->prevNoiseU32[i]; // Q(prevQNoise+11)
tmpU32no3 = 0;
if ((tmpU32no1) && (nonSpeechProbFinal[i])) {
// This value will be used later, if gammaNoise changes
tmpU32no3 = WEBRTC_SPL_UMUL_32_16(tmpU32no1, nonSpeechProbFinal[i]); // Q(prevQNoise+8)
if (0x7c000000 & tmpU32no3) {
// Shifting required before multiplication
tmpU32no2 = (tmpU32no3 >> 5) * gammaNoise; // Q(prevQNoise+11)
} else {
// We can do shifting after multiplication
tmpU32no2 = (tmpU32no3 * gammaNoise) >> 5; // Q(prevQNoise+11)
}
if (sign > 0) {
noiseUpdateU32 += tmpU32no2; // Q(prevQNoise+11)
} else {
// This operation is safe. We can never get wrap around, since worst
// case scenario means magnU16 = 0
noiseUpdateU32 -= tmpU32no2; // Q(prevQNoise+11)
}
}
//increase gamma (i.e., less noise update) for frame likely to be speech
prevGammaNoise = gammaNoise;
gammaNoise = NOISE_UPDATE_Q8;
//time-constant based on speech/noise state
//increase gamma (i.e., less noise update) for frames likely to be speech
if (nonSpeechProbFinal[i] < ONE_MINUS_PROB_RANGE_Q8) {
gammaNoise = GAMMA_NOISE_TRANS_AND_SPEECH_Q8;
}
if (prevGammaNoise != gammaNoise) {
// new noise update
// this line is the same as above, only that the result is stored in a different variable and the gammaNoise
// has changed
//
// noiseUpdate = noisePrev[i] + (1 - gammaNoise) * nonSpeechProb * (magn[i] - noisePrev[i])
if (0x7c000000 & tmpU32no3) {
// Shifting required before multiplication
tmpU32no2 = (tmpU32no3 >> 5) * gammaNoise; // Q(prevQNoise+11)
} else {
// We can do shifting after multiplication
tmpU32no2 = (tmpU32no3 * gammaNoise) >> 5; // Q(prevQNoise+11)
}
if (sign > 0) {
tmpU32no1 = inst->prevNoiseU32[i] + tmpU32no2; // Q(prevQNoise+11)
} else {
tmpU32no1 = inst->prevNoiseU32[i] - tmpU32no2; // Q(prevQNoise+11)
}
if (noiseUpdateU32 > tmpU32no1) {
noiseUpdateU32 = tmpU32no1; // Q(prevQNoise+11)
}
}
noiseU32[i] = noiseUpdateU32; // Q(prevQNoise+11)
if (noiseUpdateU32 > maxNoiseU32) {
maxNoiseU32 = noiseUpdateU32;
}
// conservative noise update
// // original FLOAT code
// if (prob_speech < PROB_RANGE) {
// inst->avgMagnPause[i] = inst->avgMagnPause[i] + (1.0 - gamma_pause)*(magn[i] - inst->avgMagnPause[i]);
// }
tmp32no2 = WEBRTC_SPL_SHIFT_W32(inst->avgMagnPause[i], -nShifts);
if (nonSpeechProbFinal[i] > ONE_MINUS_PROB_RANGE_Q8) {
if (nShifts < 0) {
tmp32no1 = (int32_t)magnU16[i] - tmp32no2; // Q(qMagn)
tmp32no1 *= ONE_MINUS_GAMMA_PAUSE_Q8; // Q(8+prevQMagn+nShifts)
tmp32no1 = (tmp32no1 + 128) >> 8; // Q(qMagn).
} else {
// In Q(qMagn+nShifts)
tmp32no1 = ((int32_t)magnU16[i] << nShifts) - inst->avgMagnPause[i];
tmp32no1 *= ONE_MINUS_GAMMA_PAUSE_Q8; // Q(8+prevQMagn+nShifts)
tmp32no1 = (tmp32no1 + (128 << nShifts)) >> (8 + nShifts); // Q(qMagn).
}
tmp32no2 += tmp32no1; // Q(qMagn)
}
inst->avgMagnPause[i] = tmp32no2;
} // end of frequency loop
norm32no1 = WebRtcSpl_NormU32(maxNoiseU32);
qNoise = inst->prevQNoise + norm32no1 - 5;
// done with step 2: noise update
// STEP 3: compute dd update of prior snr and post snr based on new noise estimate
nShifts = inst->prevQNoise + 11 - qMagn;
for (i = 0; i < inst->magnLen; i++) {
// FLOAT code
// // post and prior SNR
// curNearSnr = 0.0;
// if (magn[i] > noise[i])
// {
// curNearSnr = magn[i] / (noise[i] + 0.0001) - 1.0;
// }
// // DD estimate is sum of two terms: current estimate and previous estimate
// // directed decision update of snrPrior
// snrPrior = DD_PR_SNR * prevNearSnr[i] + (1.0 - DD_PR_SNR) * curNearSnr;
// // gain filter
// tmpFloat1 = inst->overdrive + snrPrior;
// tmpFloat2 = snrPrior / tmpFloat1;
// theFilter[i] = tmpFloat2;
// calculate curNearSnr again, this is necessary because a new noise estimate has been made since then. for the original
curNearSnr = 0; // Q11
if (nShifts < 0) {
// This case is equivalent with magn < noise which implies curNearSnr = 0;
tmpMagnU32 = (uint32_t)magnU16[i]; // Q(qMagn)
tmpNoiseU32 = noiseU32[i] << -nShifts; // Q(qMagn)
} else if (nShifts > 17) {
tmpMagnU32 = (uint32_t)magnU16[i] << 17; // Q(qMagn+17)
tmpNoiseU32 = noiseU32[i] >> (nShifts - 17); // Q(qMagn+17)
} else {
tmpMagnU32 = (uint32_t)magnU16[i] << nShifts; // Q(qNoise_prev+11)
tmpNoiseU32 = noiseU32[i]; // Q(qNoise_prev+11)
}
if (tmpMagnU32 > tmpNoiseU32) {
tmpU32no1 = tmpMagnU32 - tmpNoiseU32; // Q(qCur)
norm32no2 = WEBRTC_SPL_MIN(11, WebRtcSpl_NormU32(tmpU32no1));
tmpU32no1 <<= norm32no2; // Q(qCur+norm32no2)
tmpU32no2 = tmpNoiseU32 >> (11 - norm32no2); // Q(qCur+norm32no2-11)
if (tmpU32no2 > 0) {
tmpU32no1 /= tmpU32no2; // Q11
}
curNearSnr = WEBRTC_SPL_MIN(satMax, tmpU32no1); // Q11
}
//directed decision update of priorSnr
// FLOAT
// priorSnr = DD_PR_SNR * prevNearSnr + (1.0-DD_PR_SNR) * curNearSnr;
tmpU32no1 = WEBRTC_SPL_UMUL_32_16(prevNearSnr[i], DD_PR_SNR_Q11); // Q22
tmpU32no2 = WEBRTC_SPL_UMUL_32_16(curNearSnr, ONE_MINUS_DD_PR_SNR_Q11); // Q22
priorSnr = tmpU32no1 + tmpU32no2; // Q22
//gain filter
tmpU32no1 = inst->overdrive + ((priorSnr + 8192) >> 14); // Q8
assert(inst->overdrive > 0);
tmpU16no1 = (priorSnr + tmpU32no1 / 2) / tmpU32no1; // Q14
inst->noiseSupFilter[i] = WEBRTC_SPL_SAT(16384, tmpU16no1, inst->denoiseBound); // 16384 = Q14(1.0) // Q14
// Weight in the parametric Wiener filter during startup
if (inst->blockIndex < END_STARTUP_SHORT) {
// Weight the two suppression filters
tmpU32no1 = inst->noiseSupFilter[i] * inst->blockIndex;
tmpU32no2 = noiseSupFilterTmp[i] *
(END_STARTUP_SHORT - inst->blockIndex);
tmpU32no1 += tmpU32no2;
inst->noiseSupFilter[i] = (uint16_t)WebRtcSpl_DivU32U16(tmpU32no1,
END_STARTUP_SHORT);
}
} // end of loop over frequencies
//done with step3
// save noise and magnitude spectrum for next frame
inst->prevQNoise = qNoise;
inst->prevQMagn = qMagn;
if (norm32no1 > 5) {
for (i = 0; i < inst->magnLen; i++) {
inst->prevNoiseU32[i] = noiseU32[i] << (norm32no1 - 5); // Q(qNoise+11)
inst->prevMagnU16[i] = magnU16[i]; // Q(qMagn)
}
} else {
for (i = 0; i < inst->magnLen; i++) {
inst->prevNoiseU32[i] = noiseU32[i] >> (5 - norm32no1); // Q(qNoise+11)
inst->prevMagnU16[i] = magnU16[i]; // Q(qMagn)
}
}
WebRtcNsx_DataSynthesis(inst, outFrame[0]);
#ifdef NS_FILEDEBUG
if (fwrite(outframe, sizeof(short),
inst->blockLen10ms, inst->outfile) != inst->blockLen10ms) {
assert(false);
}
#endif
//for H band:
// only update data buffer, then apply time-domain gain is applied derived from L band
if (num_bands > 1) {
// update analysis buffer for H band
// append new data to buffer FX
for (i = 0; i < num_high_bands; ++i) {
memcpy(inst->dataBufHBFX[i], inst->dataBufHBFX[i] + inst->blockLen10ms,
(inst->anaLen - inst->blockLen10ms) * sizeof(*inst->dataBufHBFX[i]));
memcpy(inst->dataBufHBFX[i] + inst->anaLen - inst->blockLen10ms,
speechFrameHB[i], inst->blockLen10ms * sizeof(*inst->dataBufHBFX[i]));
}
// range for averaging low band quantities for H band gain
gainTimeDomainHB = 16384; // 16384 = Q14(1.0)
//average speech prob from low band
//average filter gain from low band
//avg over second half (i.e., 4->8kHz) of freq. spectrum
tmpU32no1 = 0; // Q12
tmpU16no1 = 0; // Q8
for (i = inst->anaLen2 - (inst->anaLen2 >> 2); i < inst->anaLen2; i++) {
tmpU16no1 += nonSpeechProbFinal[i]; // Q8
tmpU32no1 += (uint32_t)(inst->noiseSupFilter[i]); // Q14
}
assert(inst->stages >= 7);
avgProbSpeechHB = (4096 - (tmpU16no1 >> (inst->stages - 7))); // Q12
avgFilterGainHB = (int16_t)(tmpU32no1 >> (inst->stages - 3)); // Q14
// // original FLOAT code
// // gain based on speech probability:
// avg_prob_speech_tt=(float)2.0*avg_prob_speech-(float)1.0;
// gain_mod=(float)0.5*((float)1.0+(float)tanh(avg_prob_speech_tt)); // between 0 and 1
// gain based on speech probability:
// original expression: "0.5 * (1 + tanh(2x-1))"
// avgProbSpeechHB has been anyway saturated to a value between 0 and 1 so the other cases don't have to be dealt with
// avgProbSpeechHB and gainModHB are in Q12, 3607 = Q12(0.880615234375) which is a zero point of
// |0.5 * (1 + tanh(2x-1)) - x| - |0.5 * (1 + tanh(2x-1)) - 0.880615234375| meaning that from that point the error of approximating
// the expression with f(x) = x would be greater than the error of approximating the expression with f(x) = 0.880615234375
// error: "|0.5 * (1 + tanh(2x-1)) - x| from x=0 to 0.880615234375" -> http://www.wolframalpha.com/input/?i=|0.5+*+(1+%2B+tanh(2x-1))+-+x|+from+x%3D0+to+0.880615234375
// and: "|0.5 * (1 + tanh(2x-1)) - 0.880615234375| from x=0.880615234375 to 1" -> http://www.wolframalpha.com/input/?i=+|0.5+*+(1+%2B+tanh(2x-1))+-+0.880615234375|+from+x%3D0.880615234375+to+1
gainModHB = WEBRTC_SPL_MIN(avgProbSpeechHB, 3607);
// // original FLOAT code
// //combine gain with low band gain
// if (avg_prob_speech < (float)0.5) {
// gain_time_domain_HB=(float)0.5*gain_mod+(float)0.5*avg_filter_gain;
// }
// else {
// gain_time_domain_HB=(float)0.25*gain_mod+(float)0.75*avg_filter_gain;
// }
//combine gain with low band gain
if (avgProbSpeechHB < 2048) {
// 2048 = Q12(0.5)
// the next two lines in float are "gain_time_domain = 0.5 * gain_mod + 0.5 * avg_filter_gain"; Q2(0.5) = 2 equals one left shift
gainTimeDomainHB = (gainModHB << 1) + (avgFilterGainHB >> 1); // Q14
} else {
// "gain_time_domain = 0.25 * gain_mod + 0.75 * agv_filter_gain;"
gainTimeDomainHB = (int16_t)((3 * avgFilterGainHB) >> 2); // 3 = Q2(0.75)
gainTimeDomainHB += gainModHB; // Q14
}
//make sure gain is within flooring range
gainTimeDomainHB
= WEBRTC_SPL_SAT(16384, gainTimeDomainHB, (int16_t)(inst->denoiseBound)); // 16384 = Q14(1.0)
//apply gain
for (i = 0; i < num_high_bands; ++i) {
for (j = 0; j < inst->blockLen10ms; j++) {
outFrameHB[i][j] = (int16_t)((gainTimeDomainHB *
inst->dataBufHBFX[i][j]) >> 14); // Q0
}
}
} // end of H band gain computation
}