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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/features_extraction.h"
#include <array>
#include "modules/audio_processing/agc2/rnn_vad/lp_residual.h"
#include "rtc_base/checks.h"
namespace webrtc {
namespace rnn_vad {
namespace {
// Generated via "B, A = scipy.signal.butter(2, 30/12000, btype='highpass')"
const BiQuadFilter::BiQuadCoefficients kHpfConfig24k = {
{0.99446179f, -1.98892358f, 0.99446179f},
{-1.98889291f, 0.98895425f}};
} // namespace
FeaturesExtractor::FeaturesExtractor()
: use_high_pass_filter_(false),
pitch_buf_24kHz_(),
pitch_buf_24kHz_view_(pitch_buf_24kHz_.GetBufferView()),
lp_residual_(kBufSize24kHz),
lp_residual_view_(lp_residual_.data(), kBufSize24kHz),
pitch_estimator_(),
reference_frame_view_(pitch_buf_24kHz_.GetMostRecentValuesView()) {
RTC_DCHECK_EQ(kBufSize24kHz, lp_residual_.size());
hpf_.Initialize(kHpfConfig24k);
Reset();
}
FeaturesExtractor::~FeaturesExtractor() = default;
void FeaturesExtractor::Reset() {
pitch_buf_24kHz_.Reset();
spectral_features_extractor_.Reset();
if (use_high_pass_filter_)
hpf_.Reset();
}
bool FeaturesExtractor::CheckSilenceComputeFeatures(
rtc::ArrayView<const float, kFrameSize10ms24kHz> samples,
rtc::ArrayView<float, kFeatureVectorSize> feature_vector) {
// Pre-processing.
if (use_high_pass_filter_) {
std::array<float, kFrameSize10ms24kHz> samples_filtered;
hpf_.Process(samples, samples_filtered);
// Feed buffer with the pre-processed version of |samples|.
pitch_buf_24kHz_.Push(samples_filtered);
} else {
// Feed buffer with |samples|.
pitch_buf_24kHz_.Push(samples);
}
// Extract the LP residual.
float lpc_coeffs[kNumLpcCoefficients];
ComputeAndPostProcessLpcCoefficients(pitch_buf_24kHz_view_, lpc_coeffs);
ComputeLpResidual(lpc_coeffs, pitch_buf_24kHz_view_, lp_residual_view_);
// Estimate pitch on the LP-residual and write the normalized pitch period
// into the output vector (normalization based on training data stats).
pitch_info_48kHz_ = pitch_estimator_.Estimate(lp_residual_view_);
feature_vector[kFeatureVectorSize - 2] =
0.01f * (static_cast<int>(pitch_info_48kHz_.period) - 300);
// Extract lagged frames (according to the estimated pitch period).
RTC_DCHECK_LE(pitch_info_48kHz_.period / 2, kMaxPitch24kHz);
auto lagged_frame = pitch_buf_24kHz_view_.subview(
kMaxPitch24kHz - pitch_info_48kHz_.period / 2, kFrameSize20ms24kHz);
// Analyze reference and lagged frames checking if silence has been detected
// and write the feature vector.
return spectral_features_extractor_.CheckSilenceComputeFeatures(
reference_frame_view_, {lagged_frame.data(), kFrameSize20ms24kHz},
{feature_vector.data() + kNumLowerBands, kNumBands - kNumLowerBands},
{feature_vector.data(), kNumLowerBands},
{feature_vector.data() + kNumBands, kNumLowerBands},
{feature_vector.data() + kNumBands + kNumLowerBands, kNumLowerBands},
{feature_vector.data() + kNumBands + 2 * kNumLowerBands, kNumLowerBands},
&feature_vector[kFeatureVectorSize - 1]);
}
} // namespace rnn_vad
} // namespace webrtc
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