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android / platform / external / webrtc / 4ff818e61467f716340a43d30a970bcb5ec31ebf / . / webrtc / modules / audio_processing / aec / aec_core.c
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/*
* 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.
*/
/*
* The core AEC algorithm, which is presented with time-aligned signals.
*/
#include "webrtc/modules/audio_processing/aec/aec_core.h"
#ifdef WEBRTC_AEC_DEBUG_DUMP
#include <stdio.h>
#endif
#include <assert.h>
#include <math.h>
#include <stddef.h> // size_t
#include <stdlib.h>
#include <string.h>
#include "webrtc/common_audio/ring_buffer.h"
#include "webrtc/common_audio/signal_processing/include/signal_processing_library.h"
#include "webrtc/modules/audio_processing/aec/aec_common.h"
#include "webrtc/modules/audio_processing/aec/aec_core_internal.h"
#include "webrtc/modules/audio_processing/aec/aec_rdft.h"
#include "webrtc/modules/audio_processing/logging/aec_logging.h"
#include "webrtc/modules/audio_processing/utility/delay_estimator_wrapper.h"
#include "webrtc/system_wrappers/include/cpu_features_wrapper.h"
#include "webrtc/typedefs.h"
// Buffer size (samples)
static const size_t kBufSizePartitions = 250; // 1 second of audio in 16 kHz.
// Metrics
static const int subCountLen = 4;
static const int countLen = 50;
static const int kDelayMetricsAggregationWindow = 1250; // 5 seconds at 16 kHz.
// Quantities to control H band scaling for SWB input
static const float cnScaleHband =
(float)0.4; // scale for comfort noise in H band
// Initial bin for averaging nlp gain in low band
static const int freqAvgIc = PART_LEN / 2;
// Matlab code to produce table:
// win = sqrt(hanning(63)); win = [0 ; win(1:32)];
// fprintf(1, '\t%.14f, %.14f, %.14f,\n', win);
ALIGN16_BEG const float ALIGN16_END WebRtcAec_sqrtHanning[65] = {
0.00000000000000f, 0.02454122852291f, 0.04906767432742f, 0.07356456359967f,
0.09801714032956f, 0.12241067519922f, 0.14673047445536f, 0.17096188876030f,
0.19509032201613f, 0.21910124015687f, 0.24298017990326f, 0.26671275747490f,
0.29028467725446f, 0.31368174039889f, 0.33688985339222f, 0.35989503653499f,
0.38268343236509f, 0.40524131400499f, 0.42755509343028f, 0.44961132965461f,
0.47139673682600f, 0.49289819222978f, 0.51410274419322f, 0.53499761988710f,
0.55557023301960f, 0.57580819141785f, 0.59569930449243f, 0.61523159058063f,
0.63439328416365f, 0.65317284295378f, 0.67155895484702f, 0.68954054473707f,
0.70710678118655f, 0.72424708295147f, 0.74095112535496f, 0.75720884650648f,
0.77301045336274f, 0.78834642762661f, 0.80320753148064f, 0.81758481315158f,
0.83146961230255f, 0.84485356524971f, 0.85772861000027f, 0.87008699110871f,
0.88192126434835f, 0.89322430119552f, 0.90398929312344f, 0.91420975570353f,
0.92387953251129f, 0.93299279883474f, 0.94154406518302f, 0.94952818059304f,
0.95694033573221f, 0.96377606579544f, 0.97003125319454f, 0.97570213003853f,
0.98078528040323f, 0.98527764238894f, 0.98917650996478f, 0.99247953459871f,
0.99518472667220f, 0.99729045667869f, 0.99879545620517f, 0.99969881869620f,
1.00000000000000f};
// Matlab code to produce table:
// weightCurve = [0 ; 0.3 * sqrt(linspace(0,1,64))' + 0.1];
// fprintf(1, '\t%.4f, %.4f, %.4f, %.4f, %.4f, %.4f,\n', weightCurve);
ALIGN16_BEG const float ALIGN16_END WebRtcAec_weightCurve[65] = {
0.0000f, 0.1000f, 0.1378f, 0.1535f, 0.1655f, 0.1756f, 0.1845f, 0.1926f,
0.2000f, 0.2069f, 0.2134f, 0.2195f, 0.2254f, 0.2309f, 0.2363f, 0.2414f,
0.2464f, 0.2512f, 0.2558f, 0.2604f, 0.2648f, 0.2690f, 0.2732f, 0.2773f,
0.2813f, 0.2852f, 0.2890f, 0.2927f, 0.2964f, 0.3000f, 0.3035f, 0.3070f,
0.3104f, 0.3138f, 0.3171f, 0.3204f, 0.3236f, 0.3268f, 0.3299f, 0.3330f,
0.3360f, 0.3390f, 0.3420f, 0.3449f, 0.3478f, 0.3507f, 0.3535f, 0.3563f,
0.3591f, 0.3619f, 0.3646f, 0.3673f, 0.3699f, 0.3726f, 0.3752f, 0.3777f,
0.3803f, 0.3828f, 0.3854f, 0.3878f, 0.3903f, 0.3928f, 0.3952f, 0.3976f,
0.4000f};
// Matlab code to produce table:
// overDriveCurve = [sqrt(linspace(0,1,65))' + 1];
// fprintf(1, '\t%.4f, %.4f, %.4f, %.4f, %.4f, %.4f,\n', overDriveCurve);
ALIGN16_BEG const float ALIGN16_END WebRtcAec_overDriveCurve[65] = {
1.0000f, 1.1250f, 1.1768f, 1.2165f, 1.2500f, 1.2795f, 1.3062f, 1.3307f,
1.3536f, 1.3750f, 1.3953f, 1.4146f, 1.4330f, 1.4507f, 1.4677f, 1.4841f,
1.5000f, 1.5154f, 1.5303f, 1.5449f, 1.5590f, 1.5728f, 1.5863f, 1.5995f,
1.6124f, 1.6250f, 1.6374f, 1.6495f, 1.6614f, 1.6731f, 1.6847f, 1.6960f,
1.7071f, 1.7181f, 1.7289f, 1.7395f, 1.7500f, 1.7603f, 1.7706f, 1.7806f,
1.7906f, 1.8004f, 1.8101f, 1.8197f, 1.8292f, 1.8385f, 1.8478f, 1.8570f,
1.8660f, 1.8750f, 1.8839f, 1.8927f, 1.9014f, 1.9100f, 1.9186f, 1.9270f,
1.9354f, 1.9437f, 1.9520f, 1.9601f, 1.9682f, 1.9763f, 1.9843f, 1.9922f,
2.0000f};
// Delay Agnostic AEC parameters, still under development and may change.
static const float kDelayQualityThresholdMax = 0.07f;
static const float kDelayQualityThresholdMin = 0.01f;
static const int kInitialShiftOffset = 5;
#if !defined(WEBRTC_ANDROID)
static const int kDelayCorrectionStart = 1500; // 10 ms chunks
#endif
// Target suppression levels for nlp modes.
// log{0.001, 0.00001, 0.00000001}
static const float kTargetSupp[3] = {-6.9f, -11.5f, -18.4f};
// Two sets of parameters, one for the extended filter mode.
static const float kExtendedMinOverDrive[3] = {3.0f, 6.0f, 15.0f};
static const float kNormalMinOverDrive[3] = {1.0f, 2.0f, 5.0f};
const float WebRtcAec_kExtendedSmoothingCoefficients[2][2] = {{0.9f, 0.1f},
{0.92f, 0.08f}};
const float WebRtcAec_kNormalSmoothingCoefficients[2][2] = {{0.9f, 0.1f},
{0.93f, 0.07f}};
// Number of partitions forming the NLP's "preferred" bands.
enum {
kPrefBandSize = 24
};
#ifdef WEBRTC_AEC_DEBUG_DUMP
extern int webrtc_aec_instance_count;
#endif
WebRtcAecFilterFar WebRtcAec_FilterFar;
WebRtcAecScaleErrorSignal WebRtcAec_ScaleErrorSignal;
WebRtcAecFilterAdaptation WebRtcAec_FilterAdaptation;
WebRtcAecOverdriveAndSuppress WebRtcAec_OverdriveAndSuppress;
WebRtcAecComfortNoise WebRtcAec_ComfortNoise;
WebRtcAecSubBandCoherence WebRtcAec_SubbandCoherence;
WebRtcAecStoreAsComplex WebRtcAec_StoreAsComplex;
WebRtcAecPartitionDelay WebRtcAec_PartitionDelay;
WebRtcAecWindowData WebRtcAec_WindowData;
__inline static float MulRe(float aRe, float aIm, float bRe, float bIm) {
return aRe * bRe - aIm * bIm;
}
__inline static float MulIm(float aRe, float aIm, float bRe, float bIm) {
return aRe * bIm + aIm * bRe;
}
static int CmpFloat(const void* a, const void* b) {
const float* da = (const float*)a;
const float* db = (const float*)b;
return (*da > *db) - (*da < *db);
}
static void FilterFar(
int num_partitions,
int x_fft_buf_block_pos,
float x_fft_buf[2][kExtendedNumPartitions * PART_LEN1],
float h_fft_buf[2][kExtendedNumPartitions * PART_LEN1],
float y_fft[2][PART_LEN1]) {
int i;
for (i = 0; i < num_partitions; i++) {
int j;
int xPos = (i + x_fft_buf_block_pos) * PART_LEN1;
int pos = i * PART_LEN1;
// Check for wrap
if (i + x_fft_buf_block_pos >= num_partitions) {
xPos -= num_partitions * (PART_LEN1);
}
for (j = 0; j < PART_LEN1; j++) {
y_fft[0][j] += MulRe(x_fft_buf[0][xPos + j],
x_fft_buf[1][xPos + j],
h_fft_buf[0][pos + j],
h_fft_buf[1][pos + j]);
y_fft[1][j] += MulIm(x_fft_buf[0][xPos + j],
x_fft_buf[1][xPos + j],
h_fft_buf[0][pos + j],
h_fft_buf[1][pos + j]);
}
}
}
static void ScaleErrorSignal(int extended_filter_enabled,
float normal_mu,
float normal_error_threshold,
float x_pow[PART_LEN1],
float ef[2][PART_LEN1]) {
const float mu = extended_filter_enabled ? kExtendedMu : normal_mu;
const float error_threshold = extended_filter_enabled
? kExtendedErrorThreshold
: normal_error_threshold;
int i;
float abs_ef;
for (i = 0; i < (PART_LEN1); i++) {
ef[0][i] /= (x_pow[i] + 1e-10f);
ef[1][i] /= (x_pow[i] + 1e-10f);
abs_ef = sqrtf(ef[0][i] * ef[0][i] + ef[1][i] * ef[1][i]);
if (abs_ef > error_threshold) {
abs_ef = error_threshold / (abs_ef + 1e-10f);
ef[0][i] *= abs_ef;
ef[1][i] *= abs_ef;
}
// Stepsize factor
ef[0][i] *= mu;
ef[1][i] *= mu;
}
}
static void FilterAdaptation(
int num_partitions,
int x_fft_buf_block_pos,
float x_fft_buf[2][kExtendedNumPartitions * PART_LEN1],
float e_fft[2][PART_LEN1],
float h_fft_buf[2][kExtendedNumPartitions * PART_LEN1]) {
int i, j;
float fft[PART_LEN2];
for (i = 0; i < num_partitions; i++) {
int xPos = (i + x_fft_buf_block_pos) * (PART_LEN1);
int pos;
// Check for wrap
if (i + x_fft_buf_block_pos >= num_partitions) {
xPos -= num_partitions * PART_LEN1;
}
pos = i * PART_LEN1;
for (j = 0; j < PART_LEN; j++) {
fft[2 * j] = MulRe(x_fft_buf[0][xPos + j],
-x_fft_buf[1][xPos + j],
e_fft[0][j],
e_fft[1][j]);
fft[2 * j + 1] = MulIm(x_fft_buf[0][xPos + j],
-x_fft_buf[1][xPos + j],
e_fft[0][j],
e_fft[1][j]);
}
fft[1] = MulRe(x_fft_buf[0][xPos + PART_LEN],
-x_fft_buf[1][xPos + PART_LEN],
e_fft[0][PART_LEN],
e_fft[1][PART_LEN]);
aec_rdft_inverse_128(fft);
memset(fft + PART_LEN, 0, sizeof(float) * PART_LEN);
// fft scaling
{
float scale = 2.0f / PART_LEN2;
for (j = 0; j < PART_LEN; j++) {
fft[j] *= scale;
}
}
aec_rdft_forward_128(fft);
h_fft_buf[0][pos] += fft[0];
h_fft_buf[0][pos + PART_LEN] += fft[1];
for (j = 1; j < PART_LEN; j++) {
h_fft_buf[0][pos + j] += fft[2 * j];
h_fft_buf[1][pos + j] += fft[2 * j + 1];
}
}
}
static void OverdriveAndSuppress(AecCore* aec,
float hNl[PART_LEN1],
const float hNlFb,
float efw[2][PART_LEN1]) {
int i;
for (i = 0; i < PART_LEN1; i++) {
// Weight subbands
if (hNl[i] > hNlFb) {
hNl[i] = WebRtcAec_weightCurve[i] * hNlFb +
(1 - WebRtcAec_weightCurve[i]) * hNl[i];
}
hNl[i] = powf(hNl[i], aec->overDriveSm * WebRtcAec_overDriveCurve[i]);
// Suppress error signal
efw[0][i] *= hNl[i];
efw[1][i] *= hNl[i];
// Ooura fft returns incorrect sign on imaginary component. It matters here
// because we are making an additive change with comfort noise.
efw[1][i] *= -1;
}
}
static int PartitionDelay(const AecCore* aec) {
// Measures the energy in each filter partition and returns the partition with
// highest energy.
// TODO(bjornv): Spread computational cost by computing one partition per
// block?
float wfEnMax = 0;
int i;
int delay = 0;
for (i = 0; i < aec->num_partitions; i++) {
int j;
int pos = i * PART_LEN1;
float wfEn = 0;
for (j = 0; j < PART_LEN1; j++) {
wfEn += aec->wfBuf[0][pos + j] * aec->wfBuf[0][pos + j] +
aec->wfBuf[1][pos + j] * aec->wfBuf[1][pos + j];
}
if (wfEn > wfEnMax) {
wfEnMax = wfEn;
delay = i;
}
}
return delay;
}
// Threshold to protect against the ill-effects of a zero far-end.
const float WebRtcAec_kMinFarendPSD = 15;
// Updates the following smoothed Power Spectral Densities (PSD):
// - sd : near-end
// - se : residual echo
// - sx : far-end
// - sde : cross-PSD of near-end and residual echo
// - sxd : cross-PSD of near-end and far-end
//
// In addition to updating the PSDs, also the filter diverge state is
// determined.
static void SmoothedPSD(AecCore* aec,
float efw[2][PART_LEN1],
float dfw[2][PART_LEN1],
float xfw[2][PART_LEN1],
int* extreme_filter_divergence) {
// Power estimate smoothing coefficients.
const float* ptrGCoh = aec->extended_filter_enabled
? WebRtcAec_kExtendedSmoothingCoefficients[aec->mult - 1]
: WebRtcAec_kNormalSmoothingCoefficients[aec->mult - 1];
int i;
float sdSum = 0, seSum = 0;
for (i = 0; i < PART_LEN1; i++) {
aec->sd[i] = ptrGCoh[0] * aec->sd[i] +
ptrGCoh[1] * (dfw[0][i] * dfw[0][i] + dfw[1][i] * dfw[1][i]);
aec->se[i] = ptrGCoh[0] * aec->se[i] +
ptrGCoh[1] * (efw[0][i] * efw[0][i] + efw[1][i] * efw[1][i]);
// We threshold here to protect against the ill-effects of a zero farend.
// The threshold is not arbitrarily chosen, but balances protection and
// adverse interaction with the algorithm's tuning.
// TODO(bjornv): investigate further why this is so sensitive.
aec->sx[i] =
ptrGCoh[0] * aec->sx[i] +
ptrGCoh[1] * WEBRTC_SPL_MAX(
xfw[0][i] * xfw[0][i] + xfw[1][i] * xfw[1][i],
WebRtcAec_kMinFarendPSD);
aec->sde[i][0] =
ptrGCoh[0] * aec->sde[i][0] +
ptrGCoh[1] * (dfw[0][i] * efw[0][i] + dfw[1][i] * efw[1][i]);
aec->sde[i][1] =
ptrGCoh[0] * aec->sde[i][1] +
ptrGCoh[1] * (dfw[0][i] * efw[1][i] - dfw[1][i] * efw[0][i]);
aec->sxd[i][0] =
ptrGCoh[0] * aec->sxd[i][0] +
ptrGCoh[1] * (dfw[0][i] * xfw[0][i] + dfw[1][i] * xfw[1][i]);
aec->sxd[i][1] =
ptrGCoh[0] * aec->sxd[i][1] +
ptrGCoh[1] * (dfw[0][i] * xfw[1][i] - dfw[1][i] * xfw[0][i]);
sdSum += aec->sd[i];
seSum += aec->se[i];
}
// Divergent filter safeguard update.
aec->divergeState = (aec->divergeState ? 1.05f : 1.0f) * seSum > sdSum;
// Signal extreme filter divergence if the error is significantly larger
// than the nearend (13 dB).
*extreme_filter_divergence = (seSum > (19.95f * sdSum));
}
// Window time domain data to be used by the fft.
__inline static void WindowData(float* x_windowed, const float* x) {
int i;
for (i = 0; i < PART_LEN; i++) {
x_windowed[i] = x[i] * WebRtcAec_sqrtHanning[i];
x_windowed[PART_LEN + i] =
x[PART_LEN + i] * WebRtcAec_sqrtHanning[PART_LEN - i];
}
}
// Puts fft output data into a complex valued array.
__inline static void StoreAsComplex(const float* data,
float data_complex[2][PART_LEN1]) {
int i;
data_complex[0][0] = data[0];
data_complex[1][0] = 0;
for (i = 1; i < PART_LEN; i++) {
data_complex[0][i] = data[2 * i];
data_complex[1][i] = data[2 * i + 1];
}
data_complex[0][PART_LEN] = data[1];
data_complex[1][PART_LEN] = 0;
}
static void SubbandCoherence(AecCore* aec,
float efw[2][PART_LEN1],
float dfw[2][PART_LEN1],
float xfw[2][PART_LEN1],
float* fft,
float* cohde,
float* cohxd,
int* extreme_filter_divergence) {
int i;
SmoothedPSD(aec, efw, dfw, xfw, extreme_filter_divergence);
// Subband coherence
for (i = 0; i < PART_LEN1; i++) {
cohde[i] =
(aec->sde[i][0] * aec->sde[i][0] + aec->sde[i][1] * aec->sde[i][1]) /
(aec->sd[i] * aec->se[i] + 1e-10f);
cohxd[i] =
(aec->sxd[i][0] * aec->sxd[i][0] + aec->sxd[i][1] * aec->sxd[i][1]) /
(aec->sx[i] * aec->sd[i] + 1e-10f);
}
}
static void GetHighbandGain(const float* lambda, float* nlpGainHband) {
int i;
*nlpGainHband = (float)0.0;
for (i = freqAvgIc; i < PART_LEN1 - 1; i++) {
*nlpGainHband += lambda[i];
}
*nlpGainHband /= (float)(PART_LEN1 - 1 - freqAvgIc);
}
static void ComfortNoise(AecCore* aec,
float efw[2][PART_LEN1],
float comfortNoiseHband[2][PART_LEN1],
const float* noisePow,
const float* lambda) {
int i, num;
float rand[PART_LEN];
float noise, noiseAvg, tmp, tmpAvg;
int16_t randW16[PART_LEN];
float u[2][PART_LEN1];
const float pi2 = 6.28318530717959f;
// Generate a uniform random array on [0 1]
WebRtcSpl_RandUArray(randW16, PART_LEN, &aec->seed);
for (i = 0; i < PART_LEN; i++) {
rand[i] = ((float)randW16[i]) / 32768;
}
// Reject LF noise
u[0][0] = 0;
u[1][0] = 0;
for (i = 1; i < PART_LEN1; i++) {
tmp = pi2 * rand[i - 1];
noise = sqrtf(noisePow[i]);
u[0][i] = noise * cosf(tmp);
u[1][i] = -noise * sinf(tmp);
}
u[1][PART_LEN] = 0;
for (i = 0; i < PART_LEN1; i++) {
// This is the proper weighting to match the background noise power
tmp = sqrtf(WEBRTC_SPL_MAX(1 - lambda[i] * lambda[i], 0));
// tmp = 1 - lambda[i];
efw[0][i] += tmp * u[0][i];
efw[1][i] += tmp * u[1][i];
}
// For H band comfort noise
// TODO: don't compute noise and "tmp" twice. Use the previous results.
noiseAvg = 0.0;
tmpAvg = 0.0;
num = 0;
if (aec->num_bands > 1) {
// average noise scale
// average over second half of freq spectrum (i.e., 4->8khz)
// TODO: we shouldn't need num. We know how many elements we're summing.
for (i = PART_LEN1 >> 1; i < PART_LEN1; i++) {
num++;
noiseAvg += sqrtf(noisePow[i]);
}
noiseAvg /= (float)num;
// average nlp scale
// average over second half of freq spectrum (i.e., 4->8khz)
// TODO: we shouldn't need num. We know how many elements we're summing.
num = 0;
for (i = PART_LEN1 >> 1; i < PART_LEN1; i++) {
num++;
tmpAvg += sqrtf(WEBRTC_SPL_MAX(1 - lambda[i] * lambda[i], 0));
}
tmpAvg /= (float)num;
// Use average noise for H band
// TODO: we should probably have a new random vector here.
// Reject LF noise
u[0][0] = 0;
u[1][0] = 0;
for (i = 1; i < PART_LEN1; i++) {
tmp = pi2 * rand[i - 1];
// Use average noise for H band
u[0][i] = noiseAvg * (float)cos(tmp);
u[1][i] = -noiseAvg * (float)sin(tmp);
}
u[1][PART_LEN] = 0;
for (i = 0; i < PART_LEN1; i++) {
// Use average NLP weight for H band
comfortNoiseHband[0][i] = tmpAvg * u[0][i];
comfortNoiseHband[1][i] = tmpAvg * u[1][i];
}
} else {
memset(comfortNoiseHband, 0,
2 * PART_LEN1 * sizeof(comfortNoiseHband[0][0]));
}
}
static void InitLevel(PowerLevel* level) {
const float kBigFloat = 1E17f;
level->averagelevel = 0;
level->framelevel = 0;
level->minlevel = kBigFloat;
level->frsum = 0;
level->sfrsum = 0;
level->frcounter = 0;
level->sfrcounter = 0;
}
static void InitStats(Stats* stats) {
stats->instant = kOffsetLevel;
stats->average = kOffsetLevel;
stats->max = kOffsetLevel;
stats->min = kOffsetLevel * (-1);
stats->sum = 0;
stats->hisum = 0;
stats->himean = kOffsetLevel;
stats->counter = 0;
stats->hicounter = 0;
}
static void InitMetrics(AecCore* self) {
self->stateCounter = 0;
InitLevel(&self->farlevel);
InitLevel(&self->nearlevel);
InitLevel(&self->linoutlevel);
InitLevel(&self->nlpoutlevel);
InitStats(&self->erl);
InitStats(&self->erle);
InitStats(&self->aNlp);
InitStats(&self->rerl);
}
static void UpdateLevel(PowerLevel* level, float in[2][PART_LEN1]) {
// Do the energy calculation in the frequency domain. The FFT is performed on
// a segment of PART_LEN2 samples due to overlap, but we only want the energy
// of half that data (the last PART_LEN samples). Parseval's relation states
// that the energy is preserved according to
//
// \sum_{n=0}^{N-1} |x(n)|^2 = 1/N * \sum_{n=0}^{N-1} |X(n)|^2
// = ENERGY,
//
// where N = PART_LEN2. Since we are only interested in calculating the energy
// for the last PART_LEN samples we approximate by calculating ENERGY and
// divide by 2,
//
// \sum_{n=N/2}^{N-1} |x(n)|^2 ~= ENERGY / 2
//
// Since we deal with real valued time domain signals we only store frequency
// bins [0, PART_LEN], which is what |in| consists of. To calculate ENERGY we
// need to add the contribution from the missing part in
// [PART_LEN+1, PART_LEN2-1]. These values are, up to a phase shift, identical
// with the values in [1, PART_LEN-1], hence multiply those values by 2. This
// is the values in the for loop below, but multiplication by 2 and division
// by 2 cancel.
// TODO(bjornv): Investigate reusing energy calculations performed at other
// places in the code.
int k = 1;
// Imaginary parts are zero at end points and left out of the calculation.
float energy = (in[0][0] * in[0][0]) / 2;
energy += (in[0][PART_LEN] * in[0][PART_LEN]) / 2;
for (k = 1; k < PART_LEN; k++) {
energy += (in[0][k] * in[0][k] + in[1][k] * in[1][k]);
}
energy /= PART_LEN2;
level->sfrsum += energy;
level->sfrcounter++;
if (level->sfrcounter > subCountLen) {
level->framelevel = level->sfrsum / (subCountLen * PART_LEN);
level->sfrsum = 0;
level->sfrcounter = 0;
if (level->framelevel > 0) {
if (level->framelevel < level->minlevel) {
level->minlevel = level->framelevel; // New minimum.
} else {
level->minlevel *= (1 + 0.001f); // Small increase.
}
}
level->frcounter++;
level->frsum += level->framelevel;
if (level->frcounter > countLen) {
level->averagelevel = level->frsum / countLen;
level->frsum = 0;
level->frcounter = 0;
}
}
}
static void UpdateMetrics(AecCore* aec) {
float dtmp, dtmp2;
const float actThresholdNoisy = 8.0f;
const float actThresholdClean = 40.0f;
const float safety = 0.99995f;
const float noisyPower = 300000.0f;
float actThreshold;
float echo, suppressedEcho;
if (aec->echoState) { // Check if echo is likely present
aec->stateCounter++;
}
if (aec->farlevel.frcounter == 0) {
if (aec->farlevel.minlevel < noisyPower) {
actThreshold = actThresholdClean;
} else {
actThreshold = actThresholdNoisy;
}
if ((aec->stateCounter > (0.5f * countLen * subCountLen)) &&
(aec->farlevel.sfrcounter == 0)
// Estimate in active far-end segments only
&&
(aec->farlevel.averagelevel >
(actThreshold * aec->farlevel.minlevel))) {
// Subtract noise power
echo = aec->nearlevel.averagelevel - safety * aec->nearlevel.minlevel;
// ERL
dtmp = 10 * (float)log10(aec->farlevel.averagelevel /
aec->nearlevel.averagelevel +
1e-10f);
dtmp2 = 10 * (float)log10(aec->farlevel.averagelevel / echo + 1e-10f);
aec->erl.instant = dtmp;
if (dtmp > aec->erl.max) {
aec->erl.max = dtmp;
}
if (dtmp < aec->erl.min) {
aec->erl.min = dtmp;
}
aec->erl.counter++;
aec->erl.sum += dtmp;
aec->erl.average = aec->erl.sum / aec->erl.counter;
// Upper mean
if (dtmp > aec->erl.average) {
aec->erl.hicounter++;
aec->erl.hisum += dtmp;
aec->erl.himean = aec->erl.hisum / aec->erl.hicounter;
}
// A_NLP
dtmp = 10 * (float)log10(aec->nearlevel.averagelevel /
(2 * aec->linoutlevel.averagelevel) +
1e-10f);
// subtract noise power
suppressedEcho = 2 * (aec->linoutlevel.averagelevel -
safety * aec->linoutlevel.minlevel);
dtmp2 = 10 * (float)log10(echo / suppressedEcho + 1e-10f);
aec->aNlp.instant = dtmp2;
if (dtmp > aec->aNlp.max) {
aec->aNlp.max = dtmp;
}
if (dtmp < aec->aNlp.min) {
aec->aNlp.min = dtmp;
}
aec->aNlp.counter++;
aec->aNlp.sum += dtmp;
aec->aNlp.average = aec->aNlp.sum / aec->aNlp.counter;
// Upper mean
if (dtmp > aec->aNlp.average) {
aec->aNlp.hicounter++;
aec->aNlp.hisum += dtmp;
aec->aNlp.himean = aec->aNlp.hisum / aec->aNlp.hicounter;
}
// ERLE
// subtract noise power
suppressedEcho = 2 * (aec->nlpoutlevel.averagelevel -
safety * aec->nlpoutlevel.minlevel);
dtmp = 10 * (float)log10(aec->nearlevel.averagelevel /
(2 * aec->nlpoutlevel.averagelevel) +
1e-10f);
dtmp2 = 10 * (float)log10(echo / suppressedEcho + 1e-10f);
dtmp = dtmp2;
aec->erle.instant = dtmp;
if (dtmp > aec->erle.max) {
aec->erle.max = dtmp;
}
if (dtmp < aec->erle.min) {
aec->erle.min = dtmp;
}
aec->erle.counter++;
aec->erle.sum += dtmp;
aec->erle.average = aec->erle.sum / aec->erle.counter;
// Upper mean
if (dtmp > aec->erle.average) {
aec->erle.hicounter++;
aec->erle.hisum += dtmp;
aec->erle.himean = aec->erle.hisum / aec->erle.hicounter;
}
}
aec->stateCounter = 0;
}
}
static void UpdateDelayMetrics(AecCore* self) {
int i = 0;
int delay_values = 0;
int median = 0;
int lookahead = WebRtc_lookahead(self->delay_estimator);
const int kMsPerBlock = PART_LEN / (self->mult * 8);
int64_t l1_norm = 0;
if (self->num_delay_values == 0) {
// We have no new delay value data. Even though -1 is a valid |median| in
// the sense that we allow negative values, it will practically never be
// used since multiples of |kMsPerBlock| will always be returned.
// We therefore use -1 to indicate in the logs that the delay estimator was
// not able to estimate the delay.
self->delay_median = -1;
self->delay_std = -1;
self->fraction_poor_delays = -1;
return;
}
// Start value for median count down.
delay_values = self->num_delay_values >> 1;
// Get median of delay values since last update.
for (i = 0; i < kHistorySizeBlocks; i++) {
delay_values -= self->delay_histogram[i];
if (delay_values < 0) {
median = i;
break;
}
}
// Account for lookahead.
self->delay_median = (median - lookahead) * kMsPerBlock;
// Calculate the L1 norm, with median value as central moment.
for (i = 0; i < kHistorySizeBlocks; i++) {
l1_norm += abs(i - median) * self->delay_histogram[i];
}
self->delay_std = (int)((l1_norm + self->num_delay_values / 2) /
self->num_delay_values) * kMsPerBlock;
// Determine fraction of delays that are out of bounds, that is, either
// negative (anti-causal system) or larger than the AEC filter length.
{
int num_delays_out_of_bounds = self->num_delay_values;
const int histogram_length = sizeof(self->delay_histogram) /
sizeof(self->delay_histogram[0]);
for (i = lookahead; i < lookahead + self->num_partitions; ++i) {
if (i < histogram_length)
num_delays_out_of_bounds -= self->delay_histogram[i];
}
self->fraction_poor_delays = (float)num_delays_out_of_bounds /
self->num_delay_values;
}
// Reset histogram.
memset(self->delay_histogram, 0, sizeof(self->delay_histogram));
self->num_delay_values = 0;
return;
}
static void ScaledInverseFft(float freq_data[2][PART_LEN1],
float time_data[PART_LEN2],
float scale,
int conjugate) {
int i;
const float normalization = scale / ((float)PART_LEN2);
const float sign = (conjugate ? -1 : 1);
time_data[0] = freq_data[0][0] * normalization;
time_data[1] = freq_data[0][PART_LEN] * normalization;
for (i = 1; i < PART_LEN; i++) {
time_data[2 * i] = freq_data[0][i] * normalization;
time_data[2 * i + 1] = sign * freq_data[1][i] * normalization;
}
aec_rdft_inverse_128(time_data);
}
static void Fft(float time_data[PART_LEN2],
float freq_data[2][PART_LEN1]) {
int i;
aec_rdft_forward_128(time_data);
// Reorder fft output data.
freq_data[1][0] = 0;
freq_data[1][PART_LEN] = 0;
freq_data[0][0] = time_data[0];
freq_data[0][PART_LEN] = time_data[1];
for (i = 1; i < PART_LEN; i++) {
freq_data[0][i] = time_data[2 * i];
freq_data[1][i] = time_data[2 * i + 1];
}
}
static int MoveFarReadPtrWithoutSystemDelayUpdate(AecCore* self, int elements) {
WebRtc_MoveReadPtr(self->far_buf_windowed, elements);
#ifdef WEBRTC_AEC_DEBUG_DUMP
WebRtc_MoveReadPtr(self->far_time_buf, elements);
#endif
return WebRtc_MoveReadPtr(self->far_buf, elements);
}
static int SignalBasedDelayCorrection(AecCore* self) {
int delay_correction = 0;
int last_delay = -2;
assert(self != NULL);
#if !defined(WEBRTC_ANDROID)
// On desktops, turn on correction after |kDelayCorrectionStart| frames. This
// is to let the delay estimation get a chance to converge. Also, if the
// playout audio volume is low (or even muted) the delay estimation can return
// a very large delay, which will break the AEC if it is applied.
if (self->frame_count < kDelayCorrectionStart) {
return 0;
}
#endif
// 1. Check for non-negative delay estimate. Note that the estimates we get
// from the delay estimation are not compensated for lookahead. Hence, a
// negative |last_delay| is an invalid one.
// 2. Verify that there is a delay change. In addition, only allow a change
// if the delay is outside a certain region taking the AEC filter length
// into account.
// TODO(bjornv): Investigate if we can remove the non-zero delay change check.
// 3. Only allow delay correction if the delay estimation quality exceeds
// |delay_quality_threshold|.
// 4. Finally, verify that the proposed |delay_correction| is feasible by
// comparing with the size of the far-end buffer.
last_delay = WebRtc_last_delay(self->delay_estimator);
if ((last_delay >= 0) &&
(last_delay != self->previous_delay) &&
(WebRtc_last_delay_quality(self->delay_estimator) >
self->delay_quality_threshold)) {
int delay = last_delay - WebRtc_lookahead(self->delay_estimator);
// Allow for a slack in the actual delay, defined by a |lower_bound| and an
// |upper_bound|. The adaptive echo cancellation filter is currently
// |num_partitions| (of 64 samples) long. If the delay estimate is negative
// or at least 3/4 of the filter length we open up for correction.
const int lower_bound = 0;
const int upper_bound = self->num_partitions * 3 / 4;
const int do_correction = delay <= lower_bound || delay > upper_bound;
if (do_correction == 1) {
int available_read = (int)WebRtc_available_read(self->far_buf);
// With |shift_offset| we gradually rely on the delay estimates. For
// positive delays we reduce the correction by |shift_offset| to lower the
// risk of pushing the AEC into a non causal state. For negative delays
// we rely on the values up to a rounding error, hence compensate by 1
// element to make sure to push the delay into the causal region.
delay_correction = -delay;
delay_correction += delay > self->shift_offset ? self->shift_offset : 1;
self->shift_offset--;
self->shift_offset = (self->shift_offset <= 1 ? 1 : self->shift_offset);
if (delay_correction > available_read - self->mult - 1) {
// There is not enough data in the buffer to perform this shift. Hence,
// we do not rely on the delay estimate and do nothing.
delay_correction = 0;
} else {
self->previous_delay = last_delay;
++self->delay_correction_count;
}
}
}
// Update the |delay_quality_threshold| once we have our first delay
// correction.
if (self->delay_correction_count > 0) {
float delay_quality = WebRtc_last_delay_quality(self->delay_estimator);
delay_quality = (delay_quality > kDelayQualityThresholdMax ?
kDelayQualityThresholdMax : delay_quality);
self->delay_quality_threshold =
(delay_quality > self->delay_quality_threshold ? delay_quality :
self->delay_quality_threshold);
}
return delay_correction;
}
static void EchoSubtraction(
AecCore* aec,
int num_partitions,
int x_fft_buf_block_pos,
int metrics_mode,
int extended_filter_enabled,
float normal_mu,
float normal_error_threshold,
float x_fft_buf[2][kExtendedNumPartitions * PART_LEN1],
float* const y,
float x_pow[PART_LEN1],
float h_fft_buf[2][kExtendedNumPartitions * PART_LEN1],
PowerLevel* linout_level,
float echo_subtractor_output[PART_LEN]) {
float s_fft[2][PART_LEN1];
float e_extended[PART_LEN2];
float s_extended[PART_LEN2];
float *s;
float e[PART_LEN];
float e_fft[2][PART_LEN1];
int i;
memset(s_fft, 0, sizeof(s_fft));
// Conditionally reset the echo subtraction filter if the filter has diverged
// significantly.
if (!aec->extended_filter_enabled &&
aec->extreme_filter_divergence) {
memset(aec->wfBuf, 0, sizeof(aec->wfBuf));
aec->extreme_filter_divergence = 0;
}
// Produce echo estimate s_fft.
WebRtcAec_FilterFar(num_partitions,
x_fft_buf_block_pos,
x_fft_buf,
h_fft_buf,
s_fft);
// Compute the time-domain echo estimate s.
ScaledInverseFft(s_fft, s_extended, 2.0f, 0);
s = &s_extended[PART_LEN];
// Compute the time-domain echo prediction error.
for (i = 0; i < PART_LEN; ++i) {
e[i] = y[i] - s[i];
}
// Compute the frequency domain echo prediction error.
memset(e_extended, 0, sizeof(float) * PART_LEN);
memcpy(e_extended + PART_LEN, e, sizeof(float) * PART_LEN);
Fft(e_extended, e_fft);
RTC_AEC_DEBUG_RAW_WRITE(aec->e_fft_file,
&e_fft[0][0],
sizeof(e_fft[0][0]) * PART_LEN1 * 2);
if (metrics_mode == 1) {
// Note that the first PART_LEN samples in fft (before transformation) are
// zero. Hence, the scaling by two in UpdateLevel() should not be
// performed. That scaling is taken care of in UpdateMetrics() instead.
UpdateLevel(linout_level, e_fft);
}
// Scale error signal inversely with far power.
WebRtcAec_ScaleErrorSignal(extended_filter_enabled,
normal_mu,
normal_error_threshold,
x_pow,
e_fft);
WebRtcAec_FilterAdaptation(num_partitions,
x_fft_buf_block_pos,
x_fft_buf,
e_fft,
h_fft_buf);
memcpy(echo_subtractor_output, e, sizeof(float) * PART_LEN);
}
static void EchoSuppression(AecCore* aec,
float* echo_subtractor_output,
float* output,
float* const* outputH) {
float efw[2][PART_LEN1];
float xfw[2][PART_LEN1];
float dfw[2][PART_LEN1];
float comfortNoiseHband[2][PART_LEN1];
float fft[PART_LEN2];
float nlpGainHband;
int i;
size_t j;
// Coherence and non-linear filter
float cohde[PART_LEN1], cohxd[PART_LEN1];
float hNlDeAvg, hNlXdAvg;
float hNl[PART_LEN1];
float hNlPref[kPrefBandSize];
float hNlFb = 0, hNlFbLow = 0;
const float prefBandQuant = 0.75f, prefBandQuantLow = 0.5f;
const int prefBandSize = kPrefBandSize / aec->mult;
const int minPrefBand = 4 / aec->mult;
// Power estimate smoothing coefficients.
const float* min_overdrive = aec->extended_filter_enabled
? kExtendedMinOverDrive
: kNormalMinOverDrive;
// Filter energy
const int delayEstInterval = 10 * aec->mult;
float* xfw_ptr = NULL;
// Update eBuf with echo subtractor output.
memcpy(aec->eBuf + PART_LEN,
echo_subtractor_output,
sizeof(float) * PART_LEN);
// Analysis filter banks for the echo suppressor.
// Windowed near-end ffts.
WindowData(fft, aec->dBuf);
aec_rdft_forward_128(fft);
StoreAsComplex(fft, dfw);
// Windowed echo suppressor output ffts.
WindowData(fft, aec->eBuf);
aec_rdft_forward_128(fft);
StoreAsComplex(fft, efw);
// We should always have at least one element stored in |far_buf|.
assert(WebRtc_available_read(aec->far_buf_windowed) > 0);
// NLP
WebRtc_ReadBuffer(aec->far_buf_windowed, (void**)&xfw_ptr, &xfw[0][0], 1);
// TODO(bjornv): Investigate if we can reuse |far_buf_windowed| instead of
// |xfwBuf|.
// Buffer far.
memcpy(aec->xfwBuf, xfw_ptr, sizeof(float) * 2 * PART_LEN1);
aec->delayEstCtr++;
if (aec->delayEstCtr == delayEstInterval) {
aec->delayEstCtr = 0;
aec->delayIdx = WebRtcAec_PartitionDelay(aec);
}
// Use delayed far.
memcpy(xfw,
aec->xfwBuf + aec->delayIdx * PART_LEN1,
sizeof(xfw[0][0]) * 2 * PART_LEN1);
WebRtcAec_SubbandCoherence(aec, efw, dfw, xfw, fft, cohde, cohxd,
&aec->extreme_filter_divergence);
// Select the microphone signal as output if the filter is deemed to have
// diverged.
if (aec->divergeState) {
memcpy(efw, dfw, sizeof(efw[0][0]) * 2 * PART_LEN1);
}
hNlXdAvg = 0;
for (i = minPrefBand; i < prefBandSize + minPrefBand; i++) {
hNlXdAvg += cohxd[i];
}
hNlXdAvg /= prefBandSize;
hNlXdAvg = 1 - hNlXdAvg;
hNlDeAvg = 0;
for (i = minPrefBand; i < prefBandSize + minPrefBand; i++) {
hNlDeAvg += cohde[i];
}
hNlDeAvg /= prefBandSize;
if (hNlXdAvg < 0.75f && hNlXdAvg < aec->hNlXdAvgMin) {
aec->hNlXdAvgMin = hNlXdAvg;
}
if (hNlDeAvg > 0.98f && hNlXdAvg > 0.9f) {
aec->stNearState = 1;
} else if (hNlDeAvg < 0.95f || hNlXdAvg < 0.8f) {
aec->stNearState = 0;
}
if (aec->hNlXdAvgMin == 1) {
aec->echoState = 0;
aec->overDrive = min_overdrive[aec->nlp_mode];
if (aec->stNearState == 1) {
memcpy(hNl, cohde, sizeof(hNl));
hNlFb = hNlDeAvg;
hNlFbLow = hNlDeAvg;
} else {
for (i = 0; i < PART_LEN1; i++) {
hNl[i] = 1 - cohxd[i];
}
hNlFb = hNlXdAvg;
hNlFbLow = hNlXdAvg;
}
} else {
if (aec->stNearState == 1) {
aec->echoState = 0;
memcpy(hNl, cohde, sizeof(hNl));
hNlFb = hNlDeAvg;
hNlFbLow = hNlDeAvg;
} else {
aec->echoState = 1;
for (i = 0; i < PART_LEN1; i++) {
hNl[i] = WEBRTC_SPL_MIN(cohde[i], 1 - cohxd[i]);
}
// Select an order statistic from the preferred bands.
// TODO: Using quicksort now, but a selection algorithm may be preferred.
memcpy(hNlPref, &hNl[minPrefBand], sizeof(float) * prefBandSize);
qsort(hNlPref, prefBandSize, sizeof(float), CmpFloat);
hNlFb = hNlPref[(int)floor(prefBandQuant * (prefBandSize - 1))];
hNlFbLow = hNlPref[(int)floor(prefBandQuantLow * (prefBandSize - 1))];
}
}
// Track the local filter minimum to determine suppression overdrive.
if (hNlFbLow < 0.6f && hNlFbLow < aec->hNlFbLocalMin) {
aec->hNlFbLocalMin = hNlFbLow;
aec->hNlFbMin = hNlFbLow;
aec->hNlNewMin = 1;
aec->hNlMinCtr = 0;
}
aec->hNlFbLocalMin =
WEBRTC_SPL_MIN(aec->hNlFbLocalMin + 0.0008f / aec->mult, 1);
aec->hNlXdAvgMin = WEBRTC_SPL_MIN(aec->hNlXdAvgMin + 0.0006f / aec->mult, 1);
if (aec->hNlNewMin == 1) {
aec->hNlMinCtr++;
}
if (aec->hNlMinCtr == 2) {
aec->hNlNewMin = 0;
aec->hNlMinCtr = 0;
aec->overDrive =
WEBRTC_SPL_MAX(kTargetSupp[aec->nlp_mode] /
((float)log(aec->hNlFbMin + 1e-10f) + 1e-10f),
min_overdrive[aec->nlp_mode]);
}
// Smooth the overdrive.
if (aec->overDrive < aec->overDriveSm) {
aec->overDriveSm = 0.99f * aec->overDriveSm + 0.01f * aec->overDrive;
} else {
aec->overDriveSm = 0.9f * aec->overDriveSm + 0.1f * aec->overDrive;
}
WebRtcAec_OverdriveAndSuppress(aec, hNl, hNlFb, efw);
// Add comfort noise.
WebRtcAec_ComfortNoise(aec, efw, comfortNoiseHband, aec->noisePow, hNl);
// TODO(bjornv): Investigate how to take the windowing below into account if
// needed.
if (aec->metricsMode == 1) {
// Note that we have a scaling by two in the time domain |eBuf|.
// In addition the time domain signal is windowed before transformation,
// losing half the energy on the average. We take care of the first
// scaling only in UpdateMetrics().
UpdateLevel(&aec->nlpoutlevel, efw);
}
// Inverse error fft.
ScaledInverseFft(efw, fft, 2.0f, 1);
// Overlap and add to obtain output.
for (i = 0; i < PART_LEN; i++) {
output[i] = (fft[i] * WebRtcAec_sqrtHanning[i] +
aec->outBuf[i] * WebRtcAec_sqrtHanning[PART_LEN - i]);
// Saturate output to keep it in the allowed range.
output[i] = WEBRTC_SPL_SAT(
WEBRTC_SPL_WORD16_MAX, output[i], WEBRTC_SPL_WORD16_MIN);
}
memcpy(aec->outBuf, &fft[PART_LEN], PART_LEN * sizeof(aec->outBuf[0]));
// For H band
if (aec->num_bands > 1) {
// H band gain
// average nlp over low band: average over second half of freq spectrum
// (4->8khz)
GetHighbandGain(hNl, &nlpGainHband);
// Inverse comfort_noise
ScaledInverseFft(comfortNoiseHband, fft, 2.0f, 0);
// compute gain factor
for (j = 0; j < aec->num_bands - 1; ++j) {
for (i = 0; i < PART_LEN; i++) {
outputH[j][i] = aec->dBufH[j][i] * nlpGainHband;
}
}
// Add some comfort noise where Hband is attenuated.
for (i = 0; i < PART_LEN; i++) {
outputH[0][i] += cnScaleHband * fft[i];
}
// Saturate output to keep it in the allowed range.
for (j = 0; j < aec->num_bands - 1; ++j) {
for (i = 0; i < PART_LEN; i++) {
outputH[j][i] = WEBRTC_SPL_SAT(
WEBRTC_SPL_WORD16_MAX, outputH[j][i], WEBRTC_SPL_WORD16_MIN);
}
}
}
// Copy the current block to the old position.
memcpy(aec->dBuf, aec->dBuf + PART_LEN, sizeof(float) * PART_LEN);
memcpy(aec->eBuf, aec->eBuf + PART_LEN, sizeof(float) * PART_LEN);
// Copy the current block to the old position for H band
for (j = 0; j < aec->num_bands - 1; ++j) {
memcpy(aec->dBufH[j], aec->dBufH[j] + PART_LEN, sizeof(float) * PART_LEN);
}
memmove(aec->xfwBuf + PART_LEN1,
aec->xfwBuf,
sizeof(aec->xfwBuf) - sizeof(complex_t) * PART_LEN1);
}
static void ProcessBlock(AecCore* aec) {
size_t i;
float fft[PART_LEN2];
float xf[2][PART_LEN1];
float df[2][PART_LEN1];
float far_spectrum = 0.0f;
float near_spectrum = 0.0f;
float abs_far_spectrum[PART_LEN1];
float abs_near_spectrum[PART_LEN1];
const float gPow[2] = {0.9f, 0.1f};
// Noise estimate constants.
const int noiseInitBlocks = 500 * aec->mult;
const float step = 0.1f;
const float ramp = 1.0002f;
const float gInitNoise[2] = {0.999f, 0.001f};
float nearend[PART_LEN];
float echo_subtractor_output[PART_LEN];
float* nearend_ptr = NULL;
float output[PART_LEN];
float outputH[NUM_HIGH_BANDS_MAX][PART_LEN];
float* outputH_ptr[NUM_HIGH_BANDS_MAX];
float* xf_ptr = NULL;
for (i = 0; i < NUM_HIGH_BANDS_MAX; ++i) {
outputH_ptr[i] = outputH[i];
}
// Concatenate old and new nearend blocks.
for (i = 0; i < aec->num_bands - 1; ++i) {
WebRtc_ReadBuffer(aec->nearFrBufH[i],
(void**)&nearend_ptr,
nearend,
PART_LEN);
memcpy(aec->dBufH[i] + PART_LEN, nearend_ptr, sizeof(nearend));
}
WebRtc_ReadBuffer(aec->nearFrBuf, (void**)&nearend_ptr, nearend, PART_LEN);
memcpy(aec->dBuf + PART_LEN, nearend_ptr, sizeof(nearend));
// ---------- Ooura fft ----------
#ifdef WEBRTC_AEC_DEBUG_DUMP
{
float farend[PART_LEN];
float* farend_ptr = NULL;
WebRtc_ReadBuffer(aec->far_time_buf, (void**)&farend_ptr, farend, 1);
RTC_AEC_DEBUG_WAV_WRITE(aec->farFile, farend_ptr, PART_LEN);
RTC_AEC_DEBUG_WAV_WRITE(aec->nearFile, nearend_ptr, PART_LEN);
}
#endif
// We should always have at least one element stored in |far_buf|.
assert(WebRtc_available_read(aec->far_buf) > 0);
WebRtc_ReadBuffer(aec->far_buf, (void**)&xf_ptr, &xf[0][0], 1);
// Near fft
memcpy(fft, aec->dBuf, sizeof(float) * PART_LEN2);
Fft(fft, df);
// Power smoothing
for (i = 0; i < PART_LEN1; i++) {
far_spectrum = (xf_ptr[i] * xf_ptr[i]) +
(xf_ptr[PART_LEN1 + i] * xf_ptr[PART_LEN1 + i]);
aec->xPow[i] =
gPow[0] * aec->xPow[i] + gPow[1] * aec->num_partitions * far_spectrum;
// Calculate absolute spectra
abs_far_spectrum[i] = sqrtf(far_spectrum);
near_spectrum = df[0][i] * df[0][i] + df[1][i] * df[1][i];
aec->dPow[i] = gPow[0] * aec->dPow[i] + gPow[1] * near_spectrum;
// Calculate absolute spectra
abs_near_spectrum[i] = sqrtf(near_spectrum);
}
// Estimate noise power. Wait until dPow is more stable.
if (aec->noiseEstCtr > 50) {
for (i = 0; i < PART_LEN1; i++) {
if (aec->dPow[i] < aec->dMinPow[i]) {
aec->dMinPow[i] =
(aec->dPow[i] + step * (aec->dMinPow[i] - aec->dPow[i])) * ramp;
} else {
aec->dMinPow[i] *= ramp;
}
}
}
// Smooth increasing noise power from zero at the start,
// to avoid a sudden burst of comfort noise.
if (aec->noiseEstCtr < noiseInitBlocks) {
aec->noiseEstCtr++;
for (i = 0; i < PART_LEN1; i++) {
if (aec->dMinPow[i] > aec->dInitMinPow[i]) {
aec->dInitMinPow[i] = gInitNoise[0] * aec->dInitMinPow[i] +
gInitNoise[1] * aec->dMinPow[i];
} else {
aec->dInitMinPow[i] = aec->dMinPow[i];
}
}
aec->noisePow = aec->dInitMinPow;
} else {
aec->noisePow = aec->dMinPow;
}
// Block wise delay estimation used for logging
if (aec->delay_logging_enabled) {
if (WebRtc_AddFarSpectrumFloat(
aec->delay_estimator_farend, abs_far_spectrum, PART_LEN1) == 0) {
int delay_estimate = WebRtc_DelayEstimatorProcessFloat(
aec->delay_estimator, abs_near_spectrum, PART_LEN1);
if (delay_estimate >= 0) {
// Update delay estimate buffer.
aec->delay_histogram[delay_estimate]++;
aec->num_delay_values++;
}
if (aec->delay_metrics_delivered == 1 &&
aec->num_delay_values >= kDelayMetricsAggregationWindow) {
UpdateDelayMetrics(aec);
}
}
}
// Update the xfBuf block position.
aec->xfBufBlockPos--;
if (aec->xfBufBlockPos == -1) {
aec->xfBufBlockPos = aec->num_partitions - 1;
}
// Buffer xf
memcpy(aec->xfBuf[0] + aec->xfBufBlockPos * PART_LEN1,
xf_ptr,
sizeof(float) * PART_LEN1);
memcpy(aec->xfBuf[1] + aec->xfBufBlockPos * PART_LEN1,
&xf_ptr[PART_LEN1],
sizeof(float) * PART_LEN1);
// Perform echo subtraction.
EchoSubtraction(aec,
aec->num_partitions,
aec->xfBufBlockPos,
aec->metricsMode,
aec->extended_filter_enabled,
aec->normal_mu,
aec->normal_error_threshold,
aec->xfBuf,
nearend_ptr,
aec->xPow,
aec->wfBuf,
&aec->linoutlevel,
echo_subtractor_output);
RTC_AEC_DEBUG_WAV_WRITE(aec->outLinearFile, echo_subtractor_output, PART_LEN);
// Perform echo suppression.
EchoSuppression(aec, echo_subtractor_output, output, outputH_ptr);
if (aec->metricsMode == 1) {
// Update power levels and echo metrics
UpdateLevel(&aec->farlevel, (float(*)[PART_LEN1])xf_ptr);
UpdateLevel(&aec->nearlevel, df);
UpdateMetrics(aec);
}
// Store the output block.
WebRtc_WriteBuffer(aec->outFrBuf, output, PART_LEN);
// For high bands
for (i = 0; i < aec->num_bands - 1; ++i) {
WebRtc_WriteBuffer(aec->outFrBufH[i], outputH[i], PART_LEN);
}
RTC_AEC_DEBUG_WAV_WRITE(aec->outFile, output, PART_LEN);
}
AecCore* WebRtcAec_CreateAec() {
int i;
AecCore* aec = malloc(sizeof(AecCore));
if (!aec) {
return NULL;
}
aec->nearFrBuf = WebRtc_CreateBuffer(FRAME_LEN + PART_LEN, sizeof(float));
if (!aec->nearFrBuf) {
WebRtcAec_FreeAec(aec);
return NULL;
}
aec->outFrBuf = WebRtc_CreateBuffer(FRAME_LEN + PART_LEN, sizeof(float));
if (!aec->outFrBuf) {
WebRtcAec_FreeAec(aec);
return NULL;
}
for (i = 0; i < NUM_HIGH_BANDS_MAX; ++i) {
aec->nearFrBufH[i] = WebRtc_CreateBuffer(FRAME_LEN + PART_LEN,
sizeof(float));
if (!aec->nearFrBufH[i]) {
WebRtcAec_FreeAec(aec);
return NULL;
}
aec->outFrBufH[i] = WebRtc_CreateBuffer(FRAME_LEN + PART_LEN,
sizeof(float));
if (!aec->outFrBufH[i]) {
WebRtcAec_FreeAec(aec);
return NULL;
}
}
// Create far-end buffers.
aec->far_buf =
WebRtc_CreateBuffer(kBufSizePartitions, sizeof(float) * 2 * PART_LEN1);
if (!aec->far_buf) {
WebRtcAec_FreeAec(aec);
return NULL;
}
aec->far_buf_windowed =
WebRtc_CreateBuffer(kBufSizePartitions, sizeof(float) * 2 * PART_LEN1);
if (!aec->far_buf_windowed) {
WebRtcAec_FreeAec(aec);
return NULL;
}
#ifdef WEBRTC_AEC_DEBUG_DUMP
aec->instance_index = webrtc_aec_instance_count;
aec->far_time_buf =
WebRtc_CreateBuffer(kBufSizePartitions, sizeof(float) * PART_LEN);
if (!aec->far_time_buf) {
WebRtcAec_FreeAec(aec);
return NULL;
}
aec->farFile = aec->nearFile = aec->outFile = aec->outLinearFile = NULL;
aec->debug_dump_count = 0;
#endif
aec->delay_estimator_farend =
WebRtc_CreateDelayEstimatorFarend(PART_LEN1, kHistorySizeBlocks);
if (aec->delay_estimator_farend == NULL) {
WebRtcAec_FreeAec(aec);
return NULL;
}
// We create the delay_estimator with the same amount of maximum lookahead as
// the delay history size (kHistorySizeBlocks) for symmetry reasons.
aec->delay_estimator = WebRtc_CreateDelayEstimator(
aec->delay_estimator_farend, kHistorySizeBlocks);
if (aec->delay_estimator == NULL) {
WebRtcAec_FreeAec(aec);
return NULL;
}
#ifdef WEBRTC_ANDROID
aec->delay_agnostic_enabled = 1; // DA-AEC enabled by default.
// DA-AEC assumes the system is causal from the beginning and will self adjust
// the lookahead when shifting is required.
WebRtc_set_lookahead(aec->delay_estimator, 0);
#else
aec->delay_agnostic_enabled = 0;
WebRtc_set_lookahead(aec->delay_estimator, kLookaheadBlocks);
#endif
aec->extended_filter_enabled = 0;
// Assembly optimization
WebRtcAec_FilterFar = FilterFar;
WebRtcAec_ScaleErrorSignal = ScaleErrorSignal;
WebRtcAec_FilterAdaptation = FilterAdaptation;
WebRtcAec_OverdriveAndSuppress = OverdriveAndSuppress;
WebRtcAec_ComfortNoise = ComfortNoise;
WebRtcAec_SubbandCoherence = SubbandCoherence;
WebRtcAec_StoreAsComplex = StoreAsComplex;
WebRtcAec_PartitionDelay = PartitionDelay;
WebRtcAec_WindowData = WindowData;
#if defined(WEBRTC_ARCH_X86_FAMILY)
if (WebRtc_GetCPUInfo(kSSE2)) {
WebRtcAec_InitAec_SSE2();
}
#endif
#if defined(MIPS_FPU_LE)
WebRtcAec_InitAec_mips();
#endif
#if defined(WEBRTC_HAS_NEON)
WebRtcAec_InitAec_neon();
#elif defined(WEBRTC_DETECT_NEON)
if ((WebRtc_GetCPUFeaturesARM() & kCPUFeatureNEON) != 0) {
WebRtcAec_InitAec_neon();
}
#endif
aec_rdft_init();
return aec;
}
void WebRtcAec_FreeAec(AecCore* aec) {
int i;
if (aec == NULL) {
return;
}
WebRtc_FreeBuffer(aec->nearFrBuf);
WebRtc_FreeBuffer(aec->outFrBuf);
for (i = 0; i < NUM_HIGH_BANDS_MAX; ++i) {
WebRtc_FreeBuffer(aec->nearFrBufH[i]);
WebRtc_FreeBuffer(aec->outFrBufH[i]);
}
WebRtc_FreeBuffer(aec->far_buf);
WebRtc_FreeBuffer(aec->far_buf_windowed);
#ifdef WEBRTC_AEC_DEBUG_DUMP
WebRtc_FreeBuffer(aec->far_time_buf);
#endif
RTC_AEC_DEBUG_WAV_CLOSE(aec->farFile);
RTC_AEC_DEBUG_WAV_CLOSE(aec->nearFile);
RTC_AEC_DEBUG_WAV_CLOSE(aec->outFile);
RTC_AEC_DEBUG_WAV_CLOSE(aec->outLinearFile);
RTC_AEC_DEBUG_RAW_CLOSE(aec->e_fft_file);
WebRtc_FreeDelayEstimator(aec->delay_estimator);
WebRtc_FreeDelayEstimatorFarend(aec->delay_estimator_farend);
free(aec);
}
int WebRtcAec_InitAec(AecCore* aec, int sampFreq) {
int i;
aec->sampFreq = sampFreq;
if (sampFreq == 8000) {
aec->normal_mu = 0.6f;
aec->normal_error_threshold = 2e-6f;
aec->num_bands = 1;
} else {
aec->normal_mu = 0.5f;
aec->normal_error_threshold = 1.5e-6f;
aec->num_bands = (size_t)(sampFreq / 16000);
}
WebRtc_InitBuffer(aec->nearFrBuf);
WebRtc_InitBuffer(aec->outFrBuf);
for (i = 0; i < NUM_HIGH_BANDS_MAX; ++i) {
WebRtc_InitBuffer(aec->nearFrBufH[i]);
WebRtc_InitBuffer(aec->outFrBufH[i]);
}
// Initialize far-end buffers.
WebRtc_InitBuffer(aec->far_buf);
WebRtc_InitBuffer(aec->far_buf_windowed);
#ifdef WEBRTC_AEC_DEBUG_DUMP
WebRtc_InitBuffer(aec->far_time_buf);
{
int process_rate = sampFreq > 16000 ? 16000 : sampFreq;
RTC_AEC_DEBUG_WAV_REOPEN("aec_far", aec->instance_index,
aec->debug_dump_count, process_rate,
&aec->farFile );
RTC_AEC_DEBUG_WAV_REOPEN("aec_near", aec->instance_index,
aec->debug_dump_count, process_rate,
&aec->nearFile);
RTC_AEC_DEBUG_WAV_REOPEN("aec_out", aec->instance_index,
aec->debug_dump_count, process_rate,
&aec->outFile );
RTC_AEC_DEBUG_WAV_REOPEN("aec_out_linear", aec->instance_index,
aec->debug_dump_count, process_rate,
&aec->outLinearFile);
}
RTC_AEC_DEBUG_RAW_OPEN("aec_e_fft",
aec->debug_dump_count,
&aec->e_fft_file);
++aec->debug_dump_count;
#endif
aec->system_delay = 0;
if (WebRtc_InitDelayEstimatorFarend(aec->delay_estimator_farend) != 0) {
return -1;
}
if (WebRtc_InitDelayEstimator(aec->delay_estimator) != 0) {
return -1;
}
aec->delay_logging_enabled = 0;
aec->delay_metrics_delivered = 0;
memset(aec->delay_histogram, 0, sizeof(aec->delay_histogram));
aec->num_delay_values = 0;
aec->delay_median = -1;
aec->delay_std = -1;
aec->fraction_poor_delays = -1.0f;
aec->signal_delay_correction = 0;
aec->previous_delay = -2; // (-2): Uninitialized.
aec->delay_correction_count = 0;
aec->shift_offset = kInitialShiftOffset;
aec->delay_quality_threshold = kDelayQualityThresholdMin;
aec->num_partitions = kNormalNumPartitions;
// Update the delay estimator with filter length. We use half the
// |num_partitions| to take the echo path into account. In practice we say
// that the echo has a duration of maximum half |num_partitions|, which is not
// true, but serves as a crude measure.
WebRtc_set_allowed_offset(aec->delay_estimator, aec->num_partitions / 2);
// TODO(bjornv): I currently hard coded the enable. Once we've established
// that AECM has no performance regression, robust_validation will be enabled
// all the time and the APIs to turn it on/off will be removed. Hence, remove
// this line then.
WebRtc_enable_robust_validation(aec->delay_estimator, 1);
aec->frame_count = 0;
// Default target suppression mode.
aec->nlp_mode = 1;
// Sampling frequency multiplier w.r.t. 8 kHz.
// In case of multiple bands we process the lower band in 16 kHz, hence the
// multiplier is always 2.
if (aec->num_bands > 1) {
aec->mult = 2;
} else {
aec->mult = (short)aec->sampFreq / 8000;
}
aec->farBufWritePos = 0;
aec->farBufReadPos = 0;
aec->inSamples = 0;
aec->outSamples = 0;
aec->knownDelay = 0;
// Initialize buffers
memset(aec->dBuf, 0, sizeof(aec->dBuf));
memset(aec->eBuf, 0, sizeof(aec->eBuf));
// For H bands
for (i = 0; i < NUM_HIGH_BANDS_MAX; ++i) {
memset(aec->dBufH[i], 0, sizeof(aec->dBufH[i]));
}
memset(aec->xPow, 0, sizeof(aec->xPow));
memset(aec->dPow, 0, sizeof(aec->dPow));
memset(aec->dInitMinPow, 0, sizeof(aec->dInitMinPow));
aec->noisePow = aec->dInitMinPow;
aec->noiseEstCtr = 0;
// Initial comfort noise power
for (i = 0; i < PART_LEN1; i++) {
aec->dMinPow[i] = 1.0e6f;
}
// Holds the last block written to
aec->xfBufBlockPos = 0;
// TODO: Investigate need for these initializations. Deleting them doesn't
// change the output at all and yields 0.4% overall speedup.
memset(aec->xfBuf, 0, sizeof(complex_t) * kExtendedNumPartitions * PART_LEN1);
memset(aec->wfBuf, 0, sizeof(complex_t) * kExtendedNumPartitions * PART_LEN1);
memset(aec->sde, 0, sizeof(complex_t) * PART_LEN1);
memset(aec->sxd, 0, sizeof(complex_t) * PART_LEN1);
memset(
aec->xfwBuf, 0, sizeof(complex_t) * kExtendedNumPartitions * PART_LEN1);
memset(aec->se, 0, sizeof(float) * PART_LEN1);
// To prevent numerical instability in the first block.
for (i = 0; i < PART_LEN1; i++) {
aec->sd[i] = 1;
}
for (i = 0; i < PART_LEN1; i++) {
aec->sx[i] = 1;
}
memset(aec->hNs, 0, sizeof(aec->hNs));
memset(aec->outBuf, 0, sizeof(float) * PART_LEN);
aec->hNlFbMin = 1;
aec->hNlFbLocalMin = 1;
aec->hNlXdAvgMin = 1;
aec->hNlNewMin = 0;
aec->hNlMinCtr = 0;
aec->overDrive = 2;
aec->overDriveSm = 2;
aec->delayIdx = 0;
aec->stNearState = 0;
aec->echoState = 0;
aec->divergeState = 0;
aec->seed = 777;
aec->delayEstCtr = 0;
aec->extreme_filter_divergence = 0;
// Metrics disabled by default
aec->metricsMode = 0;
InitMetrics(aec);
return 0;
}
void WebRtcAec_BufferFarendPartition(AecCore* aec, const float* farend) {
float fft[PART_LEN2];
float xf[2][PART_LEN1];
// Check if the buffer is full, and in that case flush the oldest data.
if (WebRtc_available_write(aec->far_buf) < 1) {
WebRtcAec_MoveFarReadPtr(aec, 1);
}
// Convert far-end partition to the frequency domain without windowing.
memcpy(fft, farend, sizeof(float) * PART_LEN2);
Fft(fft, xf);
WebRtc_WriteBuffer(aec->far_buf, &xf[0][0], 1);
// Convert far-end partition to the frequency domain with windowing.
WindowData(fft, farend);
Fft(fft, xf);
WebRtc_WriteBuffer(aec->far_buf_windowed, &xf[0][0], 1);
}
int WebRtcAec_MoveFarReadPtr(AecCore* aec, int elements) {
int elements_moved = MoveFarReadPtrWithoutSystemDelayUpdate(aec, elements);
aec->system_delay -= elements_moved * PART_LEN;
return elements_moved;
}
void WebRtcAec_ProcessFrames(AecCore* aec,
const float* const* nearend,
size_t num_bands,
size_t num_samples,
int knownDelay,
float* const* out) {
size_t i, j;
int out_elements = 0;
aec->frame_count++;
// For each frame the process is as follows:
// 1) If the system_delay indicates on being too small for processing a
// frame we stuff the buffer with enough data for 10 ms.
// 2 a) Adjust the buffer to the system delay, by moving the read pointer.
// b) Apply signal based delay correction, if we have detected poor AEC
// performance.
// 3) TODO(bjornv): Investigate if we need to add this:
// If we can't move read pointer due to buffer size limitations we
// flush/stuff the buffer.
// 4) Process as many partitions as possible.
// 5) Update the |system_delay| with respect to a full frame of FRAME_LEN
// samples. Even though we will have data left to process (we work with
// partitions) we consider updating a whole frame, since that's the
// amount of data we input and output in audio_processing.
// 6) Update the outputs.
// The AEC has two different delay estimation algorithms built in. The
// first relies on delay input values from the user and the amount of
// shifted buffer elements is controlled by |knownDelay|. This delay will
// give a guess on how much we need to shift far-end buffers to align with
// the near-end signal. The other delay estimation algorithm uses the
// far- and near-end signals to find the offset between them. This one
// (called "signal delay") is then used to fine tune the alignment, or
// simply compensate for errors in the system based one.
// Note that the two algorithms operate independently. Currently, we only
// allow one algorithm to be turned on.
assert(aec->num_bands == num_bands);
for (j = 0; j < num_samples; j+= FRAME_LEN) {
// TODO(bjornv): Change the near-end buffer handling to be the same as for
// far-end, that is, with a near_pre_buf.
// Buffer the near-end frame.
WebRtc_WriteBuffer(aec->nearFrBuf, &nearend[0][j], FRAME_LEN);
// For H band
for (i = 1; i < num_bands; ++i) {
WebRtc_WriteBuffer(aec->nearFrBufH[i - 1], &nearend[i][j], FRAME_LEN);
}
// 1) At most we process |aec->mult|+1 partitions in 10 ms. Make sure we
// have enough far-end data for that by stuffing the buffer if the
// |system_delay| indicates others.
if (aec->system_delay < FRAME_LEN) {
// We don't have enough data so we rewind 10 ms.
WebRtcAec_MoveFarReadPtr(aec, -(aec->mult + 1));
}
if (!aec->delay_agnostic_enabled) {
// 2 a) Compensate for a possible change in the system delay.
// TODO(bjornv): Investigate how we should round the delay difference;
// right now we know that incoming |knownDelay| is underestimated when
// it's less than |aec->knownDelay|. We therefore, round (-32) in that
// direction. In the other direction, we don't have this situation, but
// might flush one partition too little. This can cause non-causality,
// which should be investigated. Maybe, allow for a non-symmetric
// rounding, like -16.
int move_elements = (aec->knownDelay - knownDelay - 32) / PART_LEN;
int moved_elements =
MoveFarReadPtrWithoutSystemDelayUpdate(aec, move_elements);
aec->knownDelay -= moved_elements * PART_LEN;
} else {
// 2 b) Apply signal based delay correction.
int move_elements = SignalBasedDelayCorrection(aec);
int moved_elements =
MoveFarReadPtrWithoutSystemDelayUpdate(aec, move_elements);
int far_near_buffer_diff = WebRtc_available_read(aec->far_buf) -
WebRtc_available_read(aec->nearFrBuf) / PART_LEN;
WebRtc_SoftResetDelayEstimator(aec->delay_estimator, moved_elements);
WebRtc_SoftResetDelayEstimatorFarend(aec->delay_estimator_farend,
moved_elements);
aec->signal_delay_correction += moved_elements;
// If we rely on reported system delay values only, a buffer underrun here
// can never occur since we've taken care of that in 1) above. Here, we
// apply signal based delay correction and can therefore end up with
// buffer underruns since the delay estimation can be wrong. We therefore
// stuff the buffer with enough elements if needed.
if (far_near_buffer_diff < 0) {
WebRtcAec_MoveFarReadPtr(aec, far_near_buffer_diff);
}
}
// 4) Process as many blocks as possible.
while (WebRtc_available_read(aec->nearFrBuf) >= PART_LEN) {
ProcessBlock(aec);
}
// 5) Update system delay with respect to the entire frame.
aec->system_delay -= FRAME_LEN;
// 6) Update output frame.
// Stuff the out buffer if we have less than a frame to output.
// This should only happen for the first frame.
out_elements = (int)WebRtc_available_read(aec->outFrBuf);
if (out_elements < FRAME_LEN) {
WebRtc_MoveReadPtr(aec->outFrBuf, out_elements - FRAME_LEN);
for (i = 0; i < num_bands - 1; ++i) {
WebRtc_MoveReadPtr(aec->outFrBufH[i], out_elements - FRAME_LEN);
}
}
// Obtain an output frame.
WebRtc_ReadBuffer(aec->outFrBuf, NULL, &out[0][j], FRAME_LEN);
// For H bands.
for (i = 1; i < num_bands; ++i) {
WebRtc_ReadBuffer(aec->outFrBufH[i - 1], NULL, &out[i][j], FRAME_LEN);
}
}
}
int WebRtcAec_GetDelayMetricsCore(AecCore* self, int* median, int* std,
float* fraction_poor_delays) {
assert(self != NULL);
assert(median != NULL);
assert(std != NULL);
if (self->delay_logging_enabled == 0) {
// Logging disabled.
return -1;
}
if (self->delay_metrics_delivered == 0) {
UpdateDelayMetrics(self);
self->delay_metrics_delivered = 1;
}
*median = self->delay_median;
*std = self->delay_std;
*fraction_poor_delays = self->fraction_poor_delays;
return 0;
}
int WebRtcAec_echo_state(AecCore* self) { return self->echoState; }
void WebRtcAec_GetEchoStats(AecCore* self,
Stats* erl,
Stats* erle,
Stats* a_nlp) {
assert(erl != NULL);
assert(erle != NULL);
assert(a_nlp != NULL);
*erl = self->erl;
*erle = self->erle;
*a_nlp = self->aNlp;
}
#ifdef WEBRTC_AEC_DEBUG_DUMP
void* WebRtcAec_far_time_buf(AecCore* self) { return self->far_time_buf; }
#endif
void WebRtcAec_SetConfigCore(AecCore* self,
int nlp_mode,
int metrics_mode,
int delay_logging) {
assert(nlp_mode >= 0 && nlp_mode < 3);
self->nlp_mode = nlp_mode;
self->metricsMode = metrics_mode;
if (self->metricsMode) {
InitMetrics(self);
}
// Turn on delay logging if it is either set explicitly or if delay agnostic
// AEC is enabled (which requires delay estimates).
self->delay_logging_enabled = delay_logging || self->delay_agnostic_enabled;
if (self->delay_logging_enabled) {
memset(self->delay_histogram, 0, sizeof(self->delay_histogram));
}
}
void WebRtcAec_enable_delay_agnostic(AecCore* self, int enable) {
self->delay_agnostic_enabled = enable;
}
int WebRtcAec_delay_agnostic_enabled(AecCore* self) {
return self->delay_agnostic_enabled;
}
void WebRtcAec_enable_extended_filter(AecCore* self, int enable) {
self->extended_filter_enabled = enable;
self->num_partitions = enable ? kExtendedNumPartitions : kNormalNumPartitions;
// Update the delay estimator with filter length. See InitAEC() for details.
WebRtc_set_allowed_offset(self->delay_estimator, self->num_partitions / 2);
}
int WebRtcAec_extended_filter_enabled(AecCore* self) {
return self->extended_filter_enabled;
}
int WebRtcAec_system_delay(AecCore* self) { return self->system_delay; }
void WebRtcAec_SetSystemDelay(AecCore* self, int delay) {
assert(delay >= 0);
self->system_delay = delay;
}