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/*
* Copyright (c) 2011 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 "noise_suppression_x.h"
#include <assert.h>
#include <math.h>
#include <string.h>
#include <stdlib.h>
#include <stdio.h>
#include "cpu_features_wrapper.h"
#include "nsx_core.h"
// Skip first frequency bins during estimation. (0 <= value < 64)
static const int kStartBand = 5;
// Constants to compensate for shifting signal log(2^shifts).
const WebRtc_Word16 WebRtcNsx_kLogTable[9] = {
0, 177, 355, 532, 710, 887, 1065, 1242, 1420
};
const WebRtc_Word16 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
};
const WebRtc_Word16 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
};
static const WebRtc_Word16 kPowTableFrac[1024] = {
0, 1, 1, 2, 3, 3, 4, 5,
6, 6, 7, 8, 8, 9, 10, 10,
11, 12, 13, 13, 14, 15, 15, 16,
17, 17, 18, 19, 20, 20, 21, 22,
22, 23, 24, 25, 25, 26, 27, 27,
28, 29, 30, 30, 31, 32, 32, 33,
34, 35, 35, 36, 37, 37, 38, 39,
40, 40, 41, 42, 42, 43, 44, 45,
45, 46, 47, 48, 48, 49, 50, 50,
51, 52, 53, 53, 54, 55, 56, 56,
57, 58, 58, 59, 60, 61, 61, 62,
63, 64, 64, 65, 66, 67, 67, 68,
69, 69, 70, 71, 72, 72, 73, 74,
75, 75, 76, 77, 78, 78, 79, 80,
81, 81, 82, 83, 84, 84, 85, 86,
87, 87, 88, 89, 90, 90, 91, 92,
93, 93, 94, 95, 96, 96, 97, 98,
99, 100, 100, 101, 102, 103, 103, 104,
105, 106, 106, 107, 108, 109, 109, 110,
111, 112, 113, 113, 114, 115, 116, 116,
117, 118, 119, 119, 120, 121, 122, 123,
123, 124, 125, 126, 126, 127, 128, 129,
130, 130, 131, 132, 133, 133, 134, 135,
136, 137, 137, 138, 139, 140, 141, 141,
142, 143, 144, 144, 145, 146, 147, 148,
148, 149, 150, 151, 152, 152, 153, 154,
155, 156, 156, 157, 158, 159, 160, 160,
161, 162, 163, 164, 164, 165, 166, 167,
168, 168, 169, 170, 171, 172, 173, 173,
174, 175, 176, 177, 177, 178, 179, 180,
181, 181, 182, 183, 184, 185, 186, 186,
187, 188, 189, 190, 190, 191, 192, 193,
194, 195, 195, 196, 197, 198, 199, 200,
200, 201, 202, 203, 204, 205, 205, 206,
207, 208, 209, 210, 210, 211, 212, 213,
214, 215, 215, 216, 217, 218, 219, 220,
220, 221, 222, 223, 224, 225, 225, 226,
227, 228, 229, 230, 231, 231, 232, 233,
234, 235, 236, 237, 237, 238, 239, 240,
241, 242, 243, 243, 244, 245, 246, 247,
248, 249, 249, 250, 251, 252, 253, 254,
255, 255, 256, 257, 258, 259, 260, 261,
262, 262, 263, 264, 265, 266, 267, 268,
268, 269, 270, 271, 272, 273, 274, 275,
276, 276, 277, 278, 279, 280, 281, 282,
283, 283, 284, 285, 286, 287, 288, 289,
290, 291, 291, 292, 293, 294, 295, 296,
297, 298, 299, 299, 300, 301, 302, 303,
304, 305, 306, 307, 308, 308, 309, 310,
311, 312, 313, 314, 315, 316, 317, 318,
318, 319, 320, 321, 322, 323, 324, 325,
326, 327, 328, 328, 329, 330, 331, 332,
333, 334, 335, 336, 337, 338, 339, 339,
340, 341, 342, 343, 344, 345, 346, 347,
348, 349, 350, 351, 352, 352, 353, 354,
355, 356, 357, 358, 359, 360, 361, 362,
363, 364, 365, 366, 367, 367, 368, 369,
370, 371, 372, 373, 374, 375, 376, 377,
378, 379, 380, 381, 382, 383, 384, 385,
385, 386, 387, 388, 389, 390, 391, 392,
393, 394, 395, 396, 397, 398, 399, 400,
401, 402, 403, 404, 405, 406, 407, 408,
409, 410, 410, 411, 412, 413, 414, 415,
416, 417, 418, 419, 420, 421, 422, 423,
424, 425, 426, 427, 428, 429, 430, 431,
432, 433, 434, 435, 436, 437, 438, 439,
440, 441, 442, 443, 444, 445, 446, 447,
448, 449, 450, 451, 452, 453, 454, 455,
456, 457, 458, 459, 460, 461, 462, 463,
464, 465, 466, 467, 468, 469, 470, 471,
472, 473, 474, 475, 476, 477, 478, 479,
480, 481, 482, 483, 484, 485, 486, 487,
488, 489, 490, 491, 492, 493, 494, 495,
496, 498, 499, 500, 501, 502, 503, 504,
505, 506, 507, 508, 509, 510, 511, 512,
513, 514, 515, 516, 517, 518, 519, 520,
521, 522, 523, 525, 526, 527, 528, 529,
530, 531, 532, 533, 534, 535, 536, 537,
538, 539, 540, 541, 542, 544, 545, 546,
547, 548, 549, 550, 551, 552, 553, 554,
555, 556, 557, 558, 560, 561, 562, 563,
564, 565, 566, 567, 568, 569, 570, 571,
572, 574, 575, 576, 577, 578, 579, 580,
581, 582, 583, 584, 585, 587, 588, 589,
590, 591, 592, 593, 594, 595, 596, 597,
599, 600, 601, 602, 603, 604, 605, 606,
607, 608, 610, 611, 612, 613, 614, 615,
616, 617, 618, 620, 621, 622, 623, 624,
625, 626, 627, 628, 630, 631, 632, 633,
634, 635, 636, 637, 639, 640, 641, 642,
643, 644, 645, 646, 648, 649, 650, 651,
652, 653, 654, 656, 657, 658, 659, 660,
661, 662, 664, 665, 666, 667, 668, 669,
670, 672, 673, 674, 675, 676, 677, 678,
680, 681, 682, 683, 684, 685, 687, 688,
689, 690, 691, 692, 693, 695, 696, 697,
698, 699, 700, 702, 703, 704, 705, 706,
708, 709, 710, 711, 712, 713, 715, 716,
717, 718, 719, 720, 722, 723, 724, 725,
726, 728, 729, 730, 731, 732, 733, 735,
736, 737, 738, 739, 741, 742, 743, 744,
745, 747, 748, 749, 750, 751, 753, 754,
755, 756, 757, 759, 760, 761, 762, 763,
765, 766, 767, 768, 770, 771, 772, 773,
774, 776, 777, 778, 779, 780, 782, 783,
784, 785, 787, 788, 789, 790, 792, 793,
794, 795, 796, 798, 799, 800, 801, 803,
804, 805, 806, 808, 809, 810, 811, 813,
814, 815, 816, 818, 819, 820, 821, 823,
824, 825, 826, 828, 829, 830, 831, 833,
834, 835, 836, 838, 839, 840, 841, 843,
844, 845, 846, 848, 849, 850, 851, 853,
854, 855, 857, 858, 859, 860, 862, 863,
864, 866, 867, 868, 869, 871, 872, 873,
874, 876, 877, 878, 880, 881, 882, 883,
885, 886, 887, 889, 890, 891, 893, 894,
895, 896, 898, 899, 900, 902, 903, 904,
906, 907, 908, 909, 911, 912, 913, 915,
916, 917, 919, 920, 921, 923, 924, 925,
927, 928, 929, 931, 932, 933, 935, 936,
937, 938, 940, 941, 942, 944, 945, 946,
948, 949, 950, 952, 953, 955, 956, 957,
959, 960, 961, 963, 964, 965, 967, 968,
969, 971, 972, 973, 975, 976, 977, 979,
980, 981, 983, 984, 986, 987, 988, 990,
991, 992, 994, 995, 996, 998, 999, 1001,
1002, 1003, 1005, 1006, 1007, 1009, 1010, 1012,
1013, 1014, 1016, 1017, 1018, 1020, 1021, 1023
};
static const WebRtc_Word16 kIndicatorTable[17] = {
0, 2017, 3809, 5227, 6258, 6963, 7424, 7718,
7901, 8014, 8084, 8126, 8152, 8168, 8177, 8183, 8187
};
// hybrib Hanning & flat window
static const WebRtc_Word16 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 WebRtc_Word16 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 WebRtc_Word16 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 WebRtc_Word16 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 WebRtc_Word16 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 WebRtc_Word16 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 WebRtc_Word16 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 WebRtc_Word16 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 WebRtc_Word16 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 WebRtc_Word16 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
};
// Declare function pointers.
NoiseEstimation WebRtcNsx_NoiseEstimation;
PrepareSpectrum WebRtcNsx_PrepareSpectrum;
SynthesisUpdate WebRtcNsx_SynthesisUpdate;
AnalysisUpdate WebRtcNsx_AnalysisUpdate;
Denormalize WebRtcNsx_Denormalize;
CreateComplexBuffer WebRtcNsx_CreateComplexBuffer;
// Update the noise estimation information.
static void UpdateNoiseEstimate(NsxInst_t* inst, int offset) {
WebRtc_Word32 tmp32no1 = 0;
WebRtc_Word32 tmp32no2 = 0;
WebRtc_Word16 tmp16 = 0;
const WebRtc_Word16 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 = WEBRTC_SPL_MUL_16_16(kExp2Const,
inst->noiseEstLogQuantile[offset + i]);
tmp32no1 = (0x00200000 | (tmp32no2 & 0x001FFFFF)); // 2^21 + frac
tmp16 = (WebRtc_Word16) WEBRTC_SPL_RSHIFT_W32(tmp32no2, 21);
tmp16 -= 21;// shift 21 to get result in Q0
tmp16 += (WebRtc_Word16) inst->qNoise; //shift to get result in Q(qNoise)
if (tmp16 < 0) {
tmp32no1 = WEBRTC_SPL_RSHIFT_W32(tmp32no1, -tmp16);
} else {
tmp32no1 = WEBRTC_SPL_LSHIFT_W32(tmp32no1, tmp16);
}
inst->noiseEstQuantile[i] = WebRtcSpl_SatW32ToW16(tmp32no1);
}
}
// Noise Estimation
static void NoiseEstimationC(NsxInst_t* inst,
uint16_t* magn,
uint32_t* noise,
int16_t* q_noise) {
WebRtc_Word16 lmagn[HALF_ANAL_BLOCKL], counter, countDiv;
WebRtc_Word16 countProd, delta, zeros, frac;
WebRtc_Word16 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((WebRtc_UWord32)magn[i]);
frac = (WebRtc_Word16)((((WebRtc_UWord32)magn[i] << zeros)
& 0x7FFFFFFF) >> 23);
// log2(magn(i))
assert(frac < 256);
log2 = (WebRtc_Word16)(((31 - zeros) << 8)
+ WebRtcNsx_kLogTableFrac[frac]);
// log2(magn(i))*log(2)
lmagn[i] = (WebRtc_Word16)WEBRTC_SPL_MUL_16_16_RSFT(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 = (WebRtc_Word16)WEBRTC_SPL_MUL_16_16(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 = (WebRtc_Word16)WEBRTC_SPL_MUL_16_16_RSFT(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;
tmp16no1 = WEBRTC_SPL_RSHIFT_W16(tmp16, 2);
inst->noiseEstLogQuantile[offset + i] += tmp16no1;
} else {
tmp16 += 1;
tmp16no1 = WEBRTC_SPL_RSHIFT_W16(tmp16, 1);
// *(1-QUANTILE), in Q2 QUANTILE=0.25, 1-0.25=0.75=3 in Q2
tmp16no2 = (WebRtc_Word16)WEBRTC_SPL_MUL_16_16_RSFT(tmp16no1, 3, 1);
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 = (WebRtc_Word16)WEBRTC_SPL_MUL_16_16_RSFT_WITH_ROUND(
inst->noiseEstDensity[offset + i], countProd, 15);
tmp16no2 = (WebRtc_Word16)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] = (WebRtc_UWord32)(inst->noiseEstQuantile[i]); // Q(qNoise)
}
(*q_noise) = (WebRtc_Word16)inst->qNoise;
}
// Filter the data in the frequency domain, and create spectrum.
static void PrepareSpectrumC(NsxInst_t* inst, int16_t* freq_buf) {
int i = 0, j = 0;
int16_t tmp16 = 0;
for (i = 0; i < inst->magnLen; i++) {
inst->real[i] = (WebRtc_Word16)WEBRTC_SPL_MUL_16_16_RSFT(inst->real[i],
(WebRtc_Word16)(inst->noiseSupFilter[i]), 14); // Q(normData-stages)
inst->imag[i] = (WebRtc_Word16)WEBRTC_SPL_MUL_16_16_RSFT(inst->imag[i],
(WebRtc_Word16)(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) {
tmp16 = (inst->anaLen << 1) - j;
freq_buf[j] = inst->real[i];
freq_buf[j + 1] = -inst->imag[i];
freq_buf[tmp16] = inst->real[i];
freq_buf[tmp16 + 1] = inst->imag[i];
}
freq_buf[inst->anaLen] = inst->real[inst->anaLen2];
freq_buf[inst->anaLen + 1] = -inst->imag[inst->anaLen2];
}
// Denormalize the input buffer.
static __inline void DenormalizeC(NsxInst_t* inst, int16_t* in, int factor) {
int i = 0, j = 0;
int32_t tmp32 = 0;
for (i = 0, j = 0; i < inst->anaLen; i += 1, j += 2) {
tmp32 = WEBRTC_SPL_SHIFT_W32((WebRtc_Word32)in[j],
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(NsxInst_t* 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] = WEBRTC_SPL_ADD_SAT_W16(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
WEBRTC_SPL_MEMCPY_W16(inst->synthesisBuffer,
inst->synthesisBuffer + inst->blockLen10ms,
inst->anaLen - inst->blockLen10ms);
WebRtcSpl_ZerosArrayW16(inst->synthesisBuffer
+ inst->anaLen - inst->blockLen10ms, inst->blockLen10ms);
}
// Update analysis buffer for lower band, and window data before FFT.
static void AnalysisUpdateC(NsxInst_t* inst,
int16_t* out,
int16_t* new_speech) {
int i = 0;
// For lower band update analysis buffer.
WEBRTC_SPL_MEMCPY_W16(inst->analysisBuffer,
inst->analysisBuffer + inst->blockLen10ms,
inst->anaLen - inst->blockLen10ms);
WEBRTC_SPL_MEMCPY_W16(inst->analysisBuffer
+ inst->anaLen - inst->blockLen10ms, new_speech, inst->blockLen10ms);
// 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
}
}
// Create a complex number buffer (out[]) as the intput (in[]) interleaved with
// zeros, and normalize it.
static __inline void CreateComplexBufferC(NsxInst_t* inst,
int16_t* in,
int16_t* out) {
int i = 0, j = 0;
for (i = 0, j = 0; i < inst->anaLen; i += 1, j += 2) {
out[j] = WEBRTC_SPL_LSHIFT_W16(in[i], inst->normData); // Q(normData)
out[j + 1] = 0; // Insert zeros in imaginary part
}
}
void WebRtcNsx_CalcParametricNoiseEstimate(NsxInst_t* inst,
WebRtc_Word16 pink_noise_exp_avg,
WebRtc_Word32 pink_noise_num_avg,
int freq_index,
WebRtc_UWord32* noise_estimate,
WebRtc_UWord32* noise_estimate_avg) {
WebRtc_Word32 tmp32no1 = 0;
WebRtc_Word32 tmp32no2 = 0;
WebRtc_Word16 int_part = 0;
WebRtc_Word16 frac_part = 0;
// Use pink noise estimate
// noise_estimate = 2^(pinkNoiseNumerator + pinkNoiseExp * log2(j))
assert(freq_index >= 0);
assert(freq_index < 129);
tmp32no2 = WEBRTC_SPL_MUL_16_16(pink_noise_exp_avg, kLogIndex[freq_index]); // Q26
tmp32no2 = WEBRTC_SPL_RSHIFT_W32(tmp32no2, 15); // Q11
tmp32no1 = pink_noise_num_avg - tmp32no2; // Q11
// Calculate output: 2^tmp32no1
// Output in Q(minNorm-stages)
tmp32no1 += WEBRTC_SPL_LSHIFT_W32((WebRtc_Word32)(inst->minNorm - inst->stages), 11);
if (tmp32no1 > 0) {
int_part = (WebRtc_Word16)WEBRTC_SPL_RSHIFT_W32(tmp32no1, 11);
frac_part = (WebRtc_Word16)(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 (WEBRTC_SPL_RSHIFT_W16(frac_part, 10)) {
// Upper fractional part
tmp32no2 = WEBRTC_SPL_MUL_16_16(2048 - frac_part, 1244); // Q21
tmp32no2 = 2048 - WEBRTC_SPL_RSHIFT_W32(tmp32no2, 10);
} else {
// Lower fractional part
tmp32no2 = WEBRTC_SPL_RSHIFT_W32(WEBRTC_SPL_MUL_16_16(frac_part, 804), 10);
}
// Shift fractional part to Q(minNorm-stages)
tmp32no2 = WEBRTC_SPL_SHIFT_W32(tmp32no2, int_part - 11);
*noise_estimate_avg = WEBRTC_SPL_LSHIFT_U32(1, int_part) + (WebRtc_UWord32)tmp32no2;
// Scale up to initMagnEst, which is not block averaged
*noise_estimate = (*noise_estimate_avg) * (WebRtc_UWord32)(inst->blockIndex + 1);
}
}
// Initialize state
WebRtc_Word32 WebRtcNsx_InitCore(NsxInst_t* inst, WebRtc_UWord32 fs) {
int i;
//check for valid pointer
if (inst == NULL) {
return -1;
}
//
// Initialization of struct
if (fs == 8000 || fs == 16000 || fs == 32000) {
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 if (fs == 16000) {
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;
} else if (fs == 32000) {
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 = WEBRTC_SPL_RSHIFT_W16(inst->anaLen, 1);
inst->magnLen = inst->anaLen2 + 1;
WebRtcSpl_ZerosArrayW16(inst->analysisBuffer, ANAL_BLOCKL_MAX);
WebRtcSpl_ZerosArrayW16(inst->synthesisBuffer, ANAL_BLOCKL_MAX);
// for HB processing
WebRtcSpl_ZerosArrayW16(inst->dataBufHBFX, 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] = (WebRtc_Word16)(END_STARTUP_LONG * (i + 1)) / SIMULT;
}
// Initialize suppression filter with ones
WebRtcSpl_MemSetW16((WebRtc_Word16*)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_CreateComplexBuffer = CreateComplexBufferC;
#ifdef WEBRTC_DETECT_ARM_NEON
uint64_t features = WebRtc_GetCPUFeaturesARM();
if ((features & kCPUFeatureNEON) != 0)
{
WebRtcNsx_InitNeon();
}
#elif defined(WEBRTC_ARCH_ARM_NEON)
WebRtcNsx_InitNeon();
#endif
inst->initFlag = 1;
return 0;
}
int WebRtcNsx_set_policy_core(NsxInst_t* 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(NsxInst_t* inst, int flag) {
WebRtc_UWord32 tmpU32;
WebRtc_UWord32 histIndex;
WebRtc_UWord32 posPeak1SpecFlatFX, posPeak2SpecFlatFX;
WebRtc_UWord32 posPeak1SpecDiffFX, posPeak2SpecDiffFX;
WebRtc_Word32 tmp32;
WebRtc_Word32 fluctLrtFX, thresFluctLrtFX;
WebRtc_Word32 avgHistLrtFX, avgSquareHistLrtFX, avgHistLrtComplFX;
WebRtc_Word16 j;
WebRtc_Word16 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 = (WebRtc_UWord32)(inst->featureLogLrt);
if (histIndex < HIST_PAR_EST) {
inst->histLrt[histIndex]++;
}
// Spectral flatness
// (inst->featureSpecFlat*20)>>10 = (inst->featureSpecFlat*5)>>8
histIndex = WEBRTC_SPL_RSHIFT_U32(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 = WEBRTC_SPL_UDIV((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 = WEBRTC_SPL_MUL_16_16(inst->histLrt[i], j);
avgHistLrtFX += tmp32;
numHistLrt += inst->histLrt[i];
avgSquareHistLrtFX += WEBRTC_SPL_MUL_32_16(tmp32, j);
}
avgHistLrtComplFX = avgHistLrtFX;
for (; i < HIST_PAR_EST; i++) {
j = (2 * i + 1);
tmp32 = WEBRTC_SPL_MUL_16_16(inst->histLrt[i], j);
avgHistLrtComplFX += tmp32;
avgSquareHistLrtFX += WEBRTC_SPL_MUL_32_16(tmp32, j);
}
fluctLrtFX = WEBRTC_SPL_MUL(avgSquareHistLrtFX, numHistLrt);
fluctLrtFX -= WEBRTC_SPL_MUL(avgHistLrtFX, avgHistLrtComplFX);
thresFluctLrtFX = THRES_FLUCT_LRT * numHistLrt;
// get threshold for LRT feature:
tmpU32 = (FACTOR_1_LRT_DIFF * (WebRtc_UWord32)avgHistLrtFX);
if ((fluctLrtFX < thresFluctLrtFX) || (numHistLrt == 0) ||
(tmpU32 > (WebRtc_UWord32)(100 * numHistLrt))) {
//very low fluctuation, so likely noise
inst->thresholdLogLrt = inst->maxLrt;
} else {
tmp32 = (WebRtc_Word32)((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 = (WebRtc_UWord32)(2 * i + 1);
} else if (inst->histSpecFlat[i] > maxPeak2) {
// Found new "second" peak
maxPeak2 = inst->histSpecFlat[i];
weightPeak2SpecFlat = inst->histSpecFlat[i];
posPeak2SpecFlatFX = (WebRtc_UWord32)(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 = (WebRtc_UWord32)(2 * i + 1);
} else if (inst->histSpecDiff[i] > maxPeak2) {
// Found new "second" peak
maxPeak2 = inst->histSpecDiff[i];
weightPeak2SpecDiff = inst->histSpecDiff[i];
posPeak2SpecDiffFX = (WebRtc_UWord32)(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(NsxInst_t* inst, WebRtc_UWord16* magn) {
WebRtc_UWord32 tmpU32;
WebRtc_UWord32 avgSpectralFlatnessNum, avgSpectralFlatnessDen;
WebRtc_Word32 tmp32;
WebRtc_Word32 currentSpectralFlatness, logCurSpectralFlatness;
WebRtc_Word16 zeros, frac, intPart;
int i;
// for flatness
avgSpectralFlatnessNum = 0;
avgSpectralFlatnessDen = inst->sumMagn - (WebRtc_UWord32)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((WebRtc_UWord32)magn[i]);
frac = (WebRtc_Word16)(((WebRtc_UWord32)((WebRtc_UWord32)(magn[i]) << zeros)
& 0x7FFFFFFF) >> 23);
// log2(magn(i))
assert(frac < 256);
tmpU32 = (WebRtc_UWord32)(((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 -= WEBRTC_SPL_RSHIFT_U32(tmpU32, 14); // Q10
return;
}
}
//ratio and inverse log: check for case of log(0)
zeros = WebRtcSpl_NormU32(avgSpectralFlatnessDen);
frac = (WebRtc_Word16)(((avgSpectralFlatnessDen << zeros) & 0x7FFFFFFF) >> 23);
// log2(avgSpectralFlatnessDen)
assert(frac < 256);
tmp32 = (WebRtc_Word32)(((31 - zeros) << 8) + WebRtcNsx_kLogTableFrac[frac]); // Q8
logCurSpectralFlatness = (WebRtc_Word32)avgSpectralFlatnessNum;
logCurSpectralFlatness += ((WebRtc_Word32)(inst->stages - 1) << (inst->stages + 7)); // Q(8+stages-1)
logCurSpectralFlatness -= (tmp32 << (inst->stages - 1));
logCurSpectralFlatness = WEBRTC_SPL_LSHIFT_W32(logCurSpectralFlatness, 10 - inst->stages); // Q17
tmp32 = (WebRtc_Word32)(0x00020000 | (WEBRTC_SPL_ABS_W32(logCurSpectralFlatness)
& 0x0001FFFF)); //Q17
intPart = -(WebRtc_Word16)WEBRTC_SPL_RSHIFT_W32(logCurSpectralFlatness, 17);
intPart += 7; // Shift 7 to get the output in Q10 (from Q17 = -17+10)
if (intPart > 0) {
currentSpectralFlatness = WEBRTC_SPL_RSHIFT_W32(tmp32, intPart);
} else {
currentSpectralFlatness = WEBRTC_SPL_LSHIFT_W32(tmp32, -intPart);
}
//time average update of spectral flatness feature
tmp32 = currentSpectralFlatness - (WebRtc_Word32)inst->featureSpecFlat; // Q10
tmp32 = WEBRTC_SPL_MUL_32_16(SPECT_FLAT_TAVG_Q14, tmp32); // Q24
inst->featureSpecFlat = (WebRtc_UWord32)((WebRtc_Word32)inst->featureSpecFlat
+ WEBRTC_SPL_RSHIFT_W32(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(NsxInst_t* inst, WebRtc_UWord16* magnIn) {
// This is to be calculated:
// avgDiffNormMagn = var(magnIn) - cov(magnIn, magnAvgPause)^2 / var(magnAvgPause)
WebRtc_UWord32 tmpU32no1, tmpU32no2;
WebRtc_UWord32 varMagnUFX, varPauseUFX, avgDiffNormMagnUFX;
WebRtc_Word32 tmp32no1, tmp32no2;
WebRtc_Word32 avgPauseFX, avgMagnFX, covMagnPauseFX;
WebRtc_Word32 maxPause, minPause;
WebRtc_Word16 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 = WEBRTC_SPL_RSHIFT_W32(avgPauseFX, inst->stages - 1);
avgMagnFX = (WebRtc_Word32)WEBRTC_SPL_RSHIFT_U32(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 = (WebRtc_Word16)((WebRtc_Word32)magnIn[i] - avgMagnFX);
tmp32no2 = inst->avgMagnPause[i] - avgPauseFX;
varMagnUFX += (WebRtc_UWord32)WEBRTC_SPL_MUL_16_16(tmp16no1, tmp16no1); // Q(2*qMagn)
tmp32no1 = WEBRTC_SPL_MUL_32_16(tmp32no2, tmp16no1); // Q(prevQMagn+qMagn)
covMagnPauseFX += tmp32no1; // Q(prevQMagn+qMagn)
tmp32no1 = WEBRTC_SPL_RSHIFT_W32(tmp32no2, nShifts); // Q(prevQMagn-minPause)
varPauseUFX += (WebRtc_UWord32)WEBRTC_SPL_MUL(tmp32no1, tmp32no1); // Q(2*(prevQMagn-minPause))
}
//update of average magnitude spectrum: Q(-2*stages) and averaging replaced by shifts
inst->curAvgMagnEnergy += WEBRTC_SPL_RSHIFT_U32(inst->magnEnergy, 2 * inst->normData
+ inst->stages - 1);
avgDiffNormMagnUFX = varMagnUFX; // Q(2*qMagn)
if ((varPauseUFX) && (covMagnPauseFX)) {
tmpU32no1 = (WebRtc_UWord32)WEBRTC_SPL_ABS_W32(covMagnPauseFX); // Q(prevQMagn+qMagn)
norm32 = WebRtcSpl_NormU32(tmpU32no1) - 16;
if (norm32 > 0) {
tmpU32no1 = WEBRTC_SPL_LSHIFT_U32(tmpU32no1, norm32); // Q(prevQMagn+qMagn+norm32)
} else {
tmpU32no1 = WEBRTC_SPL_RSHIFT_U32(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 = WEBRTC_SPL_UDIV(tmpU32no2, varPauseUFX);
tmpU32no1 = WEBRTC_SPL_RSHIFT_U32(tmpU32no1, nShifts);
// Q(2*qMagn)
avgDiffNormMagnUFX -= WEBRTC_SPL_MIN(avgDiffNormMagnUFX, tmpU32no1);
} else {
avgDiffNormMagnUFX = 0;
}
}
//normalize and compute time average update of difference feature
tmpU32no1 = WEBRTC_SPL_RSHIFT_U32(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 -= WEBRTC_SPL_RSHIFT_U32(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 += WEBRTC_SPL_RSHIFT_U32(tmpU32no2, 8); // Q(-2*stages)
}
}
// Compute speech/noise probability
// speech/noise probability is returned in: probSpeechFinal
//snrLocPrior is the prior SNR for each frequency (in Q11)
//snrLocPost is the post SNR for each frequency (in Q11)
void WebRtcNsx_SpeechNoiseProb(NsxInst_t* inst, WebRtc_UWord16* nonSpeechProbFinal,
WebRtc_UWord32* priorLocSnr, WebRtc_UWord32* postLocSnr) {
WebRtc_UWord32 zeros, num, den, tmpU32no1, tmpU32no2, tmpU32no3;
WebRtc_Word32 invLrtFX, indPriorFX, tmp32, tmp32no1, tmp32no2, besselTmpFX32;
WebRtc_Word32 frac32, logTmp;
WebRtc_Word32 logLrtTimeAvgKsumFX;
WebRtc_Word16 indPriorFX16;
WebRtc_Word16 tmp16, tmp16no1, tmp16no2, tmpIndFX, tableIndex, frac, intPart;
int i, normTmp, normTmp2, nShifts;
// compute feature based on average LR factor
// this is the average over all frequencies of the smooth log LRT
logLrtTimeAvgKsumFX = 0;
for (i = 0; i < inst->magnLen; i++) {
besselTmpFX32 = (WebRtc_Word32)postLocSnr[i]; // Q11
normTmp = WebRtcSpl_NormU32(postLocSnr[i]);
num = WEBRTC_SPL_LSHIFT_U32(postLocSnr[i], normTmp); // Q(11+normTmp)
if (normTmp > 10) {
den = WEBRTC_SPL_LSHIFT_U32(priorLocSnr[i], normTmp - 11); // Q(normTmp)
} else {
den = WEBRTC_SPL_RSHIFT_U32(priorLocSnr[i], 11 - normTmp); // Q(normTmp)
}
if (den > 0) {
besselTmpFX32 -= WEBRTC_SPL_UDIV(num, den); // Q11
} else {
besselTmpFX32 -= num; // Q11
}
// inst->logLrtTimeAvg[i] += LRT_TAVG * (besselTmp - log(snrLocPrior) - inst->logLrtTimeAvg[i]);
// Here, LRT_TAVG = 0.5
zeros = WebRtcSpl_NormU32(priorLocSnr[i]);
frac32 = (WebRtc_Word32)(((priorLocSnr[i] << zeros) & 0x7FFFFFFF) >> 19);
tmp32 = WEBRTC_SPL_MUL(frac32, frac32);
tmp32 = WEBRTC_SPL_RSHIFT_W32(WEBRTC_SPL_MUL(tmp32, -43), 19);
tmp32 += WEBRTC_SPL_MUL_16_16_RSFT((WebRtc_Word16)frac32, 5412, 12);
frac32 = tmp32 + 37;
// tmp32 = log2(priorLocSnr[i])
tmp32 = (WebRtc_Word32)(((31 - zeros) << 12) + frac32) - (11 << 12); // Q12
logTmp = WEBRTC_SPL_RSHIFT_W32(WEBRTC_SPL_MUL_32_16(tmp32, 178), 8); // log2(priorLocSnr[i])*log(2)
tmp32no1 = WEBRTC_SPL_RSHIFT_W32(logTmp + inst->logLrtTimeAvgW32[i], 1); // Q12
inst->logLrtTimeAvgW32[i] += (besselTmpFX32 - tmp32no1); // Q12
logLrtTimeAvgKsumFX += inst->logLrtTimeAvgW32[i]; // Q12
}
inst->featureLogLrt = WEBRTC_SPL_RSHIFT_W32(logLrtTimeAvgKsumFX * 5, inst->stages + 10); // 5 = BIN_SIZE_LRT / 2
// done with computation of LR factor
//
//compute the indicator functions
//
// average LRT feature
// FLOAT code
// indicator0 = 0.5 * (tanh(widthPrior * (logLrtTimeAvgKsum - threshPrior0)) + 1.0);
tmpIndFX = 16384; // Q14(1.0)
tmp32no1 = logLrtTimeAvgKsumFX - inst->thresholdLogLrt; // Q12
nShifts = 7 - inst->stages; // WIDTH_PR_MAP_SHIFT - inst->stages + 5;
//use larger width in tanh map for pause regions
if (tmp32no1 < 0) {
tmpIndFX = 0;
tmp32no1 = -tmp32no1;
//widthPrior = widthPrior * 2.0;
nShifts++;
}
tmp32no1 = WEBRTC_SPL_SHIFT_W32(tmp32no1, nShifts); // Q14
// compute indicator function: sigmoid map
tableIndex = (WebRtc_Word16)WEBRTC_SPL_RSHIFT_W32(tmp32no1, 14);
if ((tableIndex < 16) && (tableIndex >= 0)) {
tmp16no2 = kIndicatorTable[tableIndex];
tmp16no1 = kIndicatorTable[tableIndex + 1] - kIndicatorTable[tableIndex];
frac = (WebRtc_Word16)(tmp32no1 & 0x00003fff); // Q14
tmp16no2 += (WebRtc_Word16)WEBRTC_SPL_MUL_16_16_RSFT(tmp16no1, frac, 14);
if (tmpIndFX == 0) {
tmpIndFX = 8192 - tmp16no2; // Q14
} else {
tmpIndFX = 8192 + tmp16no2; // Q14
}
}
indPriorFX = WEBRTC_SPL_MUL_16_16(inst->weightLogLrt, tmpIndFX); // 6*Q14
//spectral flatness feature
if (inst->weightSpecFlat) {
tmpU32no1 = WEBRTC_SPL_UMUL(inst->featureSpecFlat, 400); // Q10
tmpIndFX = 16384; // Q14(1.0)
//use larger width in tanh map for pause regions
tmpU32no2 = inst->thresholdSpecFlat - tmpU32no1; //Q10
nShifts = 4;
if (inst->thresholdSpecFlat < tmpU32no1) {
tmpIndFX = 0;
tmpU32no2 = tmpU32no1 - inst->thresholdSpecFlat;
//widthPrior = widthPrior * 2.0;
nShifts++;
}
tmp32no1 = (WebRtc_Word32)WebRtcSpl_DivU32U16(WEBRTC_SPL_LSHIFT_U32(tmpU32no2,
nShifts), 25); //Q14
tmpU32no1 = WebRtcSpl_DivU32U16(WEBRTC_SPL_LSHIFT_U32(tmpU32no2, nShifts), 25); //Q14
// compute indicator function: sigmoid map
// FLOAT code
// indicator1 = 0.5 * (tanh(sgnMap * widthPrior * (threshPrior1 - tmpFloat1)) + 1.0);
tableIndex = (WebRtc_Word16)WEBRTC_SPL_RSHIFT_U32(tmpU32no1, 14);
if (tableIndex < 16) {
tmp16no2 = kIndicatorTable[tableIndex];
tmp16no1 = kIndicatorTable[tableIndex + 1] - kIndicatorTable[tableIndex];
frac = (WebRtc_Word16)(tmpU32no1 & 0x00003fff); // Q14
tmp16no2 += (WebRtc_Word16)WEBRTC_SPL_MUL_16_16_RSFT(tmp16no1, frac, 14);
if (tmpIndFX) {
tmpIndFX = 8192 + tmp16no2; // Q14
} else {
tmpIndFX = 8192 - tmp16no2; // Q14
}
}
indPriorFX += WEBRTC_SPL_MUL_16_16(inst->weightSpecFlat, tmpIndFX); // 6*Q14
}
//for template spectral-difference
if (inst->weightSpecDiff) {
tmpU32no1 = 0;
if (inst->featureSpecDiff) {
normTmp = WEBRTC_SPL_MIN(20 - inst->stages,
WebRtcSpl_NormU32(inst->featureSpecDiff));
tmpU32no1 = WEBRTC_SPL_LSHIFT_U32(inst->featureSpecDiff, normTmp); // Q(normTmp-2*stages)
tmpU32no2 = WEBRTC_SPL_RSHIFT_U32(inst->timeAvgMagnEnergy, 20 - inst->stages
- normTmp);
if (tmpU32no2 > 0) {
// Q(20 - inst->stages)
tmpU32no1 = WEBRTC_SPL_UDIV(tmpU32no1, tmpU32no2);
} else {
tmpU32no1 = (WebRtc_UWord32)(0x7fffffff);
}
}
tmpU32no3 = WEBRTC_SPL_UDIV(WEBRTC_SPL_LSHIFT_U32(inst->thresholdSpecDiff, 17), 25);
tmpU32no2 = tmpU32no1 - tmpU32no3;
nShifts = 1;
tmpIndFX = 16384; // Q14(1.0)
//use larger width in tanh map for pause regions
if (tmpU32no2 & 0x80000000) {
tmpIndFX = 0;
tmpU32no2 = tmpU32no3 - tmpU32no1;
//widthPrior = widthPrior * 2.0;
nShifts--;
}
tmpU32no1 = WEBRTC_SPL_RSHIFT_U32(tmpU32no2, nShifts);
// compute indicator function: sigmoid map
/* FLOAT code
indicator2 = 0.5 * (tanh(widthPrior * (tmpFloat1 - threshPrior2)) + 1.0);
*/
tableIndex = (WebRtc_Word16)WEBRTC_SPL_RSHIFT_U32(tmpU32no1, 14);
if (tableIndex < 16) {
tmp16no2 = kIndicatorTable[tableIndex];
tmp16no1 = kIndicatorTable[tableIndex + 1] - kIndicatorTable[tableIndex];
frac = (WebRtc_Word16)(tmpU32no1 & 0x00003fff); // Q14
tmp16no2 += (WebRtc_Word16)WEBRTC_SPL_MUL_16_16_RSFT_WITH_ROUND(
tmp16no1, frac, 14);
if (tmpIndFX) {
tmpIndFX = 8192 + tmp16no2;
} else {
tmpIndFX = 8192 - tmp16no2;
}
}
indPriorFX += WEBRTC_SPL_MUL_16_16(inst->weightSpecDiff, tmpIndFX); // 6*Q14
}
//combine the indicator function with the feature weights
// FLOAT code
// indPrior = 1 - (weightIndPrior0 * indicator0 + weightIndPrior1 * indicator1 + weightIndPrior2 * indicator2);
indPriorFX16 = WebRtcSpl_DivW32W16ResW16(98307 - indPriorFX, 6); // Q14
// done with computing indicator function
//compute the prior probability
// FLOAT code
// inst->priorNonSpeechProb += PRIOR_UPDATE * (indPriorNonSpeech - inst->priorNonSpeechProb);
tmp16 = indPriorFX16 - inst->priorNonSpeechProb; // Q14
inst->priorNonSpeechProb += (WebRtc_Word16)WEBRTC_SPL_MUL_16_16_RSFT(
PRIOR_UPDATE_Q14, tmp16, 14); // Q14
//final speech probability: combine prior model with LR factor:
memset(nonSpeechProbFinal, 0, sizeof(WebRtc_UWord16) * inst->magnLen);
if (inst->priorNonSpeechProb > 0) {
for (i = 0; i < inst->magnLen; i++) {
// FLOAT code
// invLrt = exp(inst->logLrtTimeAvg[i]);
// invLrt = inst->priorSpeechProb * invLrt;
// nonSpeechProbFinal[i] = (1.0 - inst->priorSpeechProb) / (1.0 - inst->priorSpeechProb + invLrt);
// invLrt = (1.0 - inst->priorNonSpeechProb) * invLrt;
// nonSpeechProbFinal[i] = inst->priorNonSpeechProb / (inst->priorNonSpeechProb + invLrt);
if (inst->logLrtTimeAvgW32[i] < 65300) {
tmp32no1 = WEBRTC_SPL_RSHIFT_W32(WEBRTC_SPL_MUL(inst->logLrtTimeAvgW32[i], 23637),
14); // Q12
intPart = (WebRtc_Word16)WEBRTC_SPL_RSHIFT_W32(tmp32no1, 12);
if (intPart < -8) {
intPart = -8;
}
frac = (WebRtc_Word16)(tmp32no1 & 0x00000fff); // Q12
// Quadratic approximation of 2^frac
tmp32no2 = WEBRTC_SPL_RSHIFT_W32(frac * frac * 44, 19); // Q12
tmp32no2 += WEBRTC_SPL_MUL_16_16_RSFT(frac, 84, 7); // Q12
invLrtFX = WEBRTC_SPL_LSHIFT_W32(1, 8 + intPart)
+ WEBRTC_SPL_SHIFT_W32(tmp32no2, intPart - 4); // Q8
normTmp = WebRtcSpl_NormW32(invLrtFX);
normTmp2 = WebRtcSpl_NormW16((16384 - inst->priorNonSpeechProb));
if (normTmp + normTmp2 >= 7) {
if (normTmp + normTmp2 < 15) {
invLrtFX = WEBRTC_SPL_RSHIFT_W32(invLrtFX, 15 - normTmp2 - normTmp);
// Q(normTmp+normTmp2-7)
tmp32no1 = WEBRTC_SPL_MUL_32_16(invLrtFX, (16384 - inst->priorNonSpeechProb));
// Q(normTmp+normTmp2+7)
invLrtFX = WEBRTC_SPL_SHIFT_W32(tmp32no1, 7 - normTmp - normTmp2); // Q14
} else {
tmp32no1 = WEBRTC_SPL_MUL_32_16(invLrtFX, (16384 - inst->priorNonSpeechProb)); // Q22
invLrtFX = WEBRTC_SPL_RSHIFT_W32(tmp32no1, 8); // Q14
}
tmp32no1 = WEBRTC_SPL_LSHIFT_W32((WebRtc_Word32)inst->priorNonSpeechProb, 8); // Q22
nonSpeechProbFinal[i] = (WebRtc_UWord16)WEBRTC_SPL_DIV(tmp32no1,
(WebRtc_Word32)inst->priorNonSpeechProb + invLrtFX); // Q8
}
}
}
}
}
// Transform input (speechFrame) to frequency domain magnitude (magnU16)
void WebRtcNsx_DataAnalysis(NsxInst_t* inst, short* speechFrame, WebRtc_UWord16* magnU16) {
WebRtc_UWord32 tmpU32no1, tmpU32no2;
WebRtc_Word32 tmp_1_w32 = 0;
WebRtc_Word32 tmp_2_w32 = 0;
WebRtc_Word32 sum_log_magn = 0;
WebRtc_Word32 sum_log_i_log_magn = 0;
WebRtc_UWord16 sum_log_magn_u16 = 0;
WebRtc_UWord16 tmp_u16 = 0;
WebRtc_Word16 sum_log_i = 0;
WebRtc_Word16 sum_log_i_square = 0;
WebRtc_Word16 frac = 0;
WebRtc_Word16 log2 = 0;
WebRtc_Word16 matrix_determinant = 0;
WebRtc_Word16 winData[ANAL_BLOCKL_MAX], maxWinData;
WebRtc_Word16 realImag[ANAL_BLOCKL_MAX << 1];
int i, j;
int zeros;
int net_norm = 0;
int right_shifts_in_magnU16 = 0;
int right_shifts_in_initMagnEst = 0;
// Update analysis buffer for lower band, and window data before FFT.
WebRtcNsx_AnalysisUpdate(inst, winData, speechFrame);
// Get input energy
inst->energyIn = WebRtcSpl_Energy(winData, (int)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_CreateComplexBuffer(inst, winData, realImag);
// bit-reverse position of elements in array and FFT the array
WebRtcSpl_ComplexBitReverse(realImag, inst->stages); // Q(normData-stages)
WebRtcSpl_ComplexFFT(realImag, inst->stages, 1);
inst->imag[0] = 0; // Q(normData-stages)
inst->imag[inst->anaLen2] = 0;
inst->real[0] = realImag[0]; // Q(normData-stages)
inst->real[inst->anaLen2] = realImag[inst->anaLen];
// Q(2*(normData-stages))
inst->magnEnergy = (WebRtc_UWord32)WEBRTC_SPL_MUL_16_16(inst->real[0], inst->real[0]);
inst->magnEnergy += (WebRtc_UWord32)WEBRTC_SPL_MUL_16_16(inst->real[inst->anaLen2],
inst->real[inst->anaLen2]);
magnU16[0] = (WebRtc_UWord16)WEBRTC_SPL_ABS_W16(inst->real[0]); // Q(normData-stages)
magnU16[inst->anaLen2] = (WebRtc_UWord16)WEBRTC_SPL_ABS_W16(inst->real[inst->anaLen2]);
inst->sumMagn = (WebRtc_UWord32)magnU16[0]; // Q(normData-stages)
inst->sumMagn += (WebRtc_UWord32)magnU16[inst->anaLen2];
if (inst->blockIndex >= END_STARTUP_SHORT) {
for (i = 1, j = 2; i < inst->anaLen2; i += 1, j += 2) {
inst->real[i] = realImag[j];
inst->imag[i] = -realImag[j + 1];
// magnitude spectrum
// energy in Q(2*(normData-stages))
tmpU32no1 = (WebRtc_UWord32)WEBRTC_SPL_MUL_16_16(realImag[j], realImag[j]);
tmpU32no1 += (WebRtc_UWord32)WEBRTC_SPL_MUL_16_16(realImag[j + 1], realImag[j + 1]);
inst->magnEnergy += tmpU32no1; // Q(2*(normData-stages))
magnU16[i] = (WebRtc_UWord16)WebRtcSpl_SqrtFloor(tmpU32no1); // Q(normData-stages)
inst->sumMagn += (WebRtc_UWord32)magnU16[i]; // Q(normData-stages)
}
} else {
//
// Gather information during startup for noise parameter estimation
//
// Switch initMagnEst to Q(minNorm-stages)
inst->initMagnEst[0] = WEBRTC_SPL_RSHIFT_U32(inst->initMagnEst[0],
right_shifts_in_initMagnEst);
inst->initMagnEst[inst->anaLen2] =
WEBRTC_SPL_RSHIFT_U32(inst->initMagnEst[inst->anaLen2],
right_shifts_in_initMagnEst); // Q(minNorm-stages)
// Shift magnU16 to same domain as initMagnEst
tmpU32no1 = WEBRTC_SPL_RSHIFT_W32((WebRtc_UWord32)magnU16[0],
right_shifts_in_magnU16); // Q(minNorm-stages)
tmpU32no2 = WEBRTC_SPL_RSHIFT_W32((WebRtc_UWord32)magnU16[inst->anaLen2],
right_shifts_in_magnU16); // Q(minNorm-stages)
// Update initMagnEst
inst->initMagnEst[0] += tmpU32no1; // Q(minNorm-stages)
inst->initMagnEst[inst->anaLen2] += tmpU32no2; // Q(minNorm-stages)
log2 = 0;
if (magnU16[inst->anaLen2]) {
// Calculate log2(magnU16[inst->anaLen2])
zeros = WebRtcSpl_NormU32((WebRtc_UWord32)magnU16[inst->anaLen2]);
frac = (WebRtc_Word16)((((WebRtc_UWord32)magnU16[inst->anaLen2] << zeros) &
0x7FFFFFFF) >> 23); // Q8
// log2(magnU16(i)) in Q8
assert(frac < 256);
log2 = (WebRtc_Word16)(((31 - zeros) << 8) + WebRtcNsx_kLogTableFrac[frac]);
}
sum_log_magn = (WebRtc_Word32)log2; // Q8
// sum_log_i_log_magn in Q17
sum_log_i_log_magn = (WEBRTC_SPL_MUL_16_16(kLogIndex[inst->anaLen2], log2) >> 3);
for (i = 1, j = 2; i < inst->anaLen2; i += 1, j += 2) {
inst->real[i] = realImag[j];
inst->imag[i] = -realImag[j + 1];
// magnitude spectrum
// energy in Q(2*(normData-stages))
tmpU32no1 = (WebRtc_UWord32)WEBRTC_SPL_MUL_16_16(realImag[j], realImag[j]);
tmpU32no1 += (WebRtc_UWord32)WEBRTC_SPL_MUL_16_16(realImag[j + 1], realImag[j + 1]);
inst->magnEnergy += tmpU32no1; // Q(2*(normData-stages))
magnU16[i] = (WebRtc_UWord16)WebRtcSpl_SqrtFloor(tmpU32no1); // Q(normData-stages)
inst->sumMagn += (WebRtc_UWord32)magnU16[i]; // Q(normData-stages)
// Switch initMagnEst to Q(minNorm-stages)
inst->initMagnEst[i] = WEBRTC_SPL_RSHIFT_U32(inst->initMagnEst[i],
right_shifts_in_initMagnEst);
// Shift magnU16 to same domain as initMagnEst, i.e., Q(minNorm-stages)
tmpU32no1 = WEBRTC_SPL_RSHIFT_W32((WebRtc_UWord32)magnU16[i],
right_shifts_in_magnU16);
// Update initMagnEst
inst->initMagnEst[i] += tmpU32no1; // Q(minNorm-stages)
if (i >= kStartBand) {
// For pink noise estimation. Collect data neglecting lower frequency band
log2 = 0;
if (magnU16[i]) {
zeros = WebRtcSpl_NormU32((WebRtc_UWord32)magnU16[i]);
frac = (WebRtc_Word16)((((WebRtc_UWord32)magnU16[i] << zeros) &
0x7FFFFFFF) >> 23);
// log2(magnU16(i)) in Q8
assert(frac < 256);
log2 = (WebRtc_Word16)(((31 - zeros) << 8)
+ WebRtcNsx_kLogTableFrac[frac]);
}
sum_log_magn += (WebRtc_Word32)log2; // Q8
// sum_log_i_log_magn in Q17
sum_log_i_log_magn += (WEBRTC_SPL_MUL_16_16(kLogIndex[i], log2) >> 3);
}
}
//
//compute simplified noise model during startup
//
// Estimate White noise
// Switch whiteNoiseLevel to Q(minNorm-stages)
inst->whiteNoiseLevel = WEBRTC_SPL_RSHIFT_U32(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 = WEBRTC_SPL_RSHIFT_U32(tmpU32no1, inst->stages + 8);
// Replacing division above with 'stages' shifts
// Shift to same Q-domain as whiteNoiseLevel
tmpU32no1 = WEBRTC_SPL_RSHIFT_U32(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 = (WebRtc_Word32)matrix_determinant;
tmp_1_w32 += WEBRTC_SPL_MUL_16_16_RSFT(kSumLogIndex[65], sum_log_i, 9);
tmp_1_w32 -= WEBRTC_SPL_MUL_16_16_RSFT(kSumLogIndex[65], kSumLogIndex[65], 10);
tmp_1_w32 -= WEBRTC_SPL_LSHIFT_W32((WebRtc_Word32)sum_log_i_square, 4);
tmp_1_w32 -= WEBRTC_SPL_MUL_16_16_RSFT((WebRtc_Word16)
(inst->magnLen - kStartBand), kSumSquareLogIndex[65], 2);
matrix_determinant = (WebRtc_Word16)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 = WEBRTC_SPL_LSHIFT_W32(sum_log_magn, 1); // Q9
sum_log_magn_u16 = (WebRtc_UWord16)WEBRTC_SPL_RSHIFT_W32(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 = WEBRTC_SPL_RSHIFT_U32((WebRtc_UWord32)sum_log_i_log_magn, 12); // Q5
// Shift the largest value of sum_log_i and tmp32no3 before multiplication
tmp_u16 = WEBRTC_SPL_LSHIFT_U16((WebRtc_UWord16)sum_log_i, 1); // Q6
if ((WebRtc_UWord32)sum_log_i > tmpU32no1) {
tmp_u16 = WEBRTC_SPL_RSHIFT_U16(tmp_u16, zeros);
} else {
tmpU32no1 = WEBRTC_SPL_RSHIFT_U32(tmpU32no1, zeros);
}
tmp_2_w32 -= (WebRtc_Word32)WEBRTC_SPL_UMUL_32_16(tmpU32no1, tmp_u16); // Q(11-zeros)
matrix_determinant = WEBRTC_SPL_RSHIFT_W16(matrix_determinant, zeros); // Q(-zeros)
tmp_2_w32 = WebRtcSpl_DivW32W16(tmp_2_w32, matrix_determinant); // Q11
tmp_2_w32 += WEBRTC_SPL_LSHIFT_W32((WebRtc_Word32)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 = WEBRTC_SPL_RSHIFT_W32(sum_log_i_log_magn, 3 + zeros);
tmp_1_w32 = WEBRTC_SPL_MUL((WebRtc_Word32)(inst->magnLen - kStartBand),
tmp_1_w32);
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(NsxInst_t* inst, short* outFrame) {
WebRtc_Word32 energyOut;
WebRtc_Word16 realImag[ANAL_BLOCKL_MAX << 1];
WebRtc_Word16 tmp16no1, tmp16no2;
WebRtc_Word16 energyRatio;
WebRtc_Word16 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
WEBRTC_SPL_MEMCPY_W16(inst->synthesisBuffer,
inst->synthesisBuffer + inst->blockLen10ms,
inst->anaLen - inst->blockLen10ms);
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);
// bit-reverse position of elements in array and IFFT it
WebRtcSpl_ComplexBitReverse(realImag, inst->stages);
outCIFFT = WebRtcSpl_ComplexIFFT(realImag, inst->stages, 1);
// Denormalize.
WebRtcNsx_Denormalize(inst, realImag, 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) {
energyOut = WebRtcSpl_Energy(inst->real, (int)inst->anaLen, &scaleEnergyOut); // Q(-scaleEnergyOut)
if (scaleEnergyOut == 0 && !(energyOut & 0x7f800000)) {
energyOut = WEBRTC_SPL_SHIFT_W32(energyOut, 8 + scaleEnergyOut
- inst->scaleEnergyIn);
} else {
inst->energyIn = WEBRTC_SPL_RSHIFT_W32(inst->energyIn, 8 + scaleEnergyOut
- inst->scaleEnergyIn); // Q(-8-scaleEnergyOut)
}
assert(inst->energyIn > 0);
energyRatio = (WebRtc_Word16)WEBRTC_SPL_DIV(energyOut
+ WEBRTC_SPL_RSHIFT_W32(inst->energyIn, 1), 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 = (WebRtc_Word16)WEBRTC_SPL_MUL_16_16_RSFT(16384 - inst->priorNonSpeechProb,
gainFactor1, 14); // Q13 16384 = Q14(1.0)
tmp16no2 = (WebRtc_Word16)WEBRTC_SPL_MUL_16_16_RSFT(inst->priorNonSpeechProb,
gainFactor2, 14); // Q13;
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);
}
int WebRtcNsx_ProcessCore(NsxInst_t* inst, short* speechFrame, short* speechFrameHB,
short* outFrame, short* outFrameHB) {
// main routine for noise suppression
WebRtc_UWord32 tmpU32no1, tmpU32no2, tmpU32no3;
WebRtc_UWord32 satMax, maxNoiseU32;
WebRtc_UWord32 tmpMagnU32, tmpNoiseU32;
WebRtc_UWord32 nearMagnEst;
WebRtc_UWord32 noiseUpdateU32;
WebRtc_UWord32 noiseU32[HALF_ANAL_BLOCKL];
WebRtc_UWord32 postLocSnr[HALF_ANAL_BLOCKL];
WebRtc_UWord32 priorLocSnr[HALF_ANAL_BLOCKL];
WebRtc_UWord32 prevNearSnr[HALF_ANAL_BLOCKL];
WebRtc_UWord32 curNearSnr;
WebRtc_UWord32 priorSnr;
WebRtc_UWord32 noise_estimate = 0;
WebRtc_UWord32 noise_estimate_avg = 0;
WebRtc_UWord32 numerator = 0;
WebRtc_Word32 tmp32no1, tmp32no2;
WebRtc_Word32 pink_noise_num_avg = 0;
WebRtc_UWord16 tmpU16no1;
WebRtc_UWord16 magnU16[HALF_ANAL_BLOCKL];
WebRtc_UWord16 prevNoiseU16[HALF_ANAL_BLOCKL];
WebRtc_UWord16 nonSpeechProbFinal[HALF_ANAL_BLOCKL];
WebRtc_UWord16 gammaNoise, prevGammaNoise;
WebRtc_UWord16 noiseSupFilterTmp[HALF_ANAL_BLOCKL];
WebRtc_Word16 qMagn, qNoise;
WebRtc_Word16 avgProbSpeechHB, gainModHB, avgFilterGainHB, gainTimeDomainHB;
WebRtc_Word16 pink_noise_exp_avg = 0;
int i;
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 % 16 == 0);
assert(inst->anaLen2 % 8 == 0);
assert(inst->blockLen10ms % 16 == 0);
assert(inst->magnLen == inst->anaLen2 + 1);
#ifdef NS_FILEDEBUG
fwrite(spframe, sizeof(short), inst->blockLen10ms, inst->infile);
#endif
// Check that initialization has been done
if (inst->initFlag != 1) {
return -1;
}
// Check for valid pointers based on sampling rate
if ((inst->fs == 32000) && (speechFrameHB == NULL)) {
return -1;
}
// Store speechFrame and transform to frequency domain
WebRtcNsx_DataAnalysis(inst, speechFrame, magnU16);
if (inst->zeroInputSignal) {
WebRtcNsx_DataSynthesis(inst, outFrame);
if (inst->fs == 32000) {
// update analysis buffer for H band
// append new data to buffer FX
WEBRTC_SPL_MEMCPY_W16(inst->dataBufHBFX, inst->dataBufHBFX + inst->blockLen10ms,
inst->anaLen - inst->blockLen10ms);
WEBRTC_SPL_MEMCPY_W16(inst->dataBufHBFX + inst->anaLen - inst->blockLen10ms,
speechFrameHB, inst->blockLen10ms);
for (i = 0; i < inst->blockLen10ms; i++) {
outFrameHB[i] = inst->dataBufHBFX[i]; // Q0
}
} // end of H band gain computation
return 0;
}
// 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] = (WebRtc_UWord16)WEBRTC_SPL_RSHIFT_U32(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 = (WebRtc_Word16)WebRtcSpl_DivW32W16(inst->pinkNoiseExp,
(WebRtc_Word16)(inst->blockIndex + 1)); // Q14
pink_noise_num_avg = WebRtcSpl_DivW32W16(inst->pinkNoiseNumerator,
(WebRtc_Word16)(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;