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/*
* Copyright (c) 2018 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 "modules/audio_processing/agc2/rnn_vad/lp_residual.h"
#include <algorithm>
#include <array>
#include <cmath>
#include <numeric>
#include "rtc_base/checks.h"
#include "rtc_base/numerics/safe_compare.h"
namespace webrtc {
namespace rnn_vad {
namespace {
// Computes auto-correlation coefficients for `x` and writes them in
// `auto_corr`. The lag values are in {0, ..., max_lag - 1}, where max_lag
// equals the size of `auto_corr`.
void ComputeAutoCorrelation(ArrayView<const float> x,
ArrayView<float, kNumLpcCoefficients> auto_corr) {
constexpr int max_lag = auto_corr.size();
RTC_DCHECK_LT(max_lag, x.size());
for (int lag = 0; lag < max_lag; ++lag) {
auto_corr[lag] =
std::inner_product(x.begin(), x.end() - lag, x.begin() + lag, 0.f);
}
}
// Applies denoising to the auto-correlation coefficients.
void DenoiseAutoCorrelation(ArrayView<float, kNumLpcCoefficients> auto_corr) {
// Assume -40 dB white noise floor.
auto_corr[0] *= 1.0001f;
// Hard-coded values obtained as
// [np.float32((0.008*0.008*i*i)) for i in range(1,5)].
auto_corr[1] -= auto_corr[1] * 0.000064f;
auto_corr[2] -= auto_corr[2] * 0.000256f;
auto_corr[3] -= auto_corr[3] * 0.000576f;
auto_corr[4] -= auto_corr[4] * 0.001024f;
static_assert(kNumLpcCoefficients == 5, "Update `auto_corr`.");
}
// Computes the initial inverse filter coefficients given the auto-correlation
// coefficients of an input frame.
void ComputeInitialInverseFilterCoefficients(
ArrayView<const float, kNumLpcCoefficients> auto_corr,
ArrayView<float, kNumLpcCoefficients - 1> lpc_coeffs) {
float error = auto_corr[0];
for (int i = 0; i < kNumLpcCoefficients - 1; ++i) {
float reflection_coeff = 0.f;
for (int j = 0; j < i; ++j) {
reflection_coeff += lpc_coeffs[j] * auto_corr[i - j];
}
reflection_coeff += auto_corr[i + 1];
// Avoid division by numbers close to zero.
constexpr float kMinErrorMagnitude = 1e-6f;
if (std::fabs(error) < kMinErrorMagnitude) {
error = std::copysign(kMinErrorMagnitude, error);
}
reflection_coeff /= -error;
// Update LPC coefficients and total error.
lpc_coeffs[i] = reflection_coeff;
for (int j = 0; j < ((i + 1) >> 1); ++j) {
const float tmp1 = lpc_coeffs[j];
const float tmp2 = lpc_coeffs[i - 1 - j];
lpc_coeffs[j] = tmp1 + reflection_coeff * tmp2;
lpc_coeffs[i - 1 - j] = tmp2 + reflection_coeff * tmp1;
}
error -= reflection_coeff * reflection_coeff * error;
if (error < 0.001f * auto_corr[0]) {
break;
}
}
}
} // namespace
void ComputeAndPostProcessLpcCoefficients(
ArrayView<const float> x,
ArrayView<float, kNumLpcCoefficients> lpc_coeffs) {
std::array<float, kNumLpcCoefficients> auto_corr;
ComputeAutoCorrelation(x, auto_corr);
if (auto_corr[0] == 0.f) { // Empty frame.
std::fill(lpc_coeffs.begin(), lpc_coeffs.end(), 0);
return;
}
DenoiseAutoCorrelation(auto_corr);
std::array<float, kNumLpcCoefficients - 1> lpc_coeffs_pre{};
ComputeInitialInverseFilterCoefficients(auto_corr, lpc_coeffs_pre);
// LPC coefficients post-processing.
// TODO(bugs.webrtc.org/9076): Consider removing these steps.
lpc_coeffs_pre[0] *= 0.9f;
lpc_coeffs_pre[1] *= 0.9f * 0.9f;
lpc_coeffs_pre[2] *= 0.9f * 0.9f * 0.9f;
lpc_coeffs_pre[3] *= 0.9f * 0.9f * 0.9f * 0.9f;
constexpr float kC = 0.8f;
lpc_coeffs[0] = lpc_coeffs_pre[0] + kC;
lpc_coeffs[1] = lpc_coeffs_pre[1] + kC * lpc_coeffs_pre[0];
lpc_coeffs[2] = lpc_coeffs_pre[2] + kC * lpc_coeffs_pre[1];
lpc_coeffs[3] = lpc_coeffs_pre[3] + kC * lpc_coeffs_pre[2];
lpc_coeffs[4] = kC * lpc_coeffs_pre[3];
static_assert(kNumLpcCoefficients == 5, "Update `lpc_coeffs(_pre)`.");
}
void ComputeLpResidual(ArrayView<const float, kNumLpcCoefficients> lpc_coeffs,
ArrayView<const float> x,
ArrayView<float> y) {
RTC_DCHECK_GT(x.size(), kNumLpcCoefficients);
RTC_DCHECK_EQ(x.size(), y.size());
// The code below implements the following operation:
// y[i] = x[i] + dot_product({x[i], ..., x[i - kNumLpcCoefficients + 1]},
// lpc_coeffs)
// Edge case: i < kNumLpcCoefficients.
y[0] = x[0];
for (int i = 1; i < kNumLpcCoefficients; ++i) {
y[i] =
std::inner_product(x.crend() - i, x.crend(), lpc_coeffs.cbegin(), x[i]);
}
// Regular case.
auto last = x.crend();
for (int i = kNumLpcCoefficients; SafeLt(i, y.size()); ++i, --last) {
y[i] = std::inner_product(last - kNumLpcCoefficients, last,
lpc_coeffs.cbegin(), x[i]);
}
}
} // namespace rnn_vad
} // namespace webrtc
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