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Diffstat (limited to 'third_party/libwebrtc/modules/audio_processing/ns/speech_probability_estimator.cc')
-rw-r--r-- | third_party/libwebrtc/modules/audio_processing/ns/speech_probability_estimator.cc | 103 |
1 files changed, 103 insertions, 0 deletions
diff --git a/third_party/libwebrtc/modules/audio_processing/ns/speech_probability_estimator.cc b/third_party/libwebrtc/modules/audio_processing/ns/speech_probability_estimator.cc new file mode 100644 index 0000000000..fce9bc8e07 --- /dev/null +++ b/third_party/libwebrtc/modules/audio_processing/ns/speech_probability_estimator.cc @@ -0,0 +1,103 @@ +/* + * Copyright (c) 2019 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/ns/speech_probability_estimator.h" + +#include <math.h> +#include <algorithm> + +#include "modules/audio_processing/ns/fast_math.h" +#include "rtc_base/checks.h" + +namespace webrtc { + +SpeechProbabilityEstimator::SpeechProbabilityEstimator() { + speech_probability_.fill(0.f); +} + +void SpeechProbabilityEstimator::Update( + int32_t num_analyzed_frames, + rtc::ArrayView<const float, kFftSizeBy2Plus1> prior_snr, + rtc::ArrayView<const float, kFftSizeBy2Plus1> post_snr, + rtc::ArrayView<const float, kFftSizeBy2Plus1> conservative_noise_spectrum, + rtc::ArrayView<const float, kFftSizeBy2Plus1> signal_spectrum, + float signal_spectral_sum, + float signal_energy) { + // Update models. + if (num_analyzed_frames < kLongStartupPhaseBlocks) { + signal_model_estimator_.AdjustNormalization(num_analyzed_frames, + signal_energy); + } + signal_model_estimator_.Update(prior_snr, post_snr, + conservative_noise_spectrum, signal_spectrum, + signal_spectral_sum, signal_energy); + + const SignalModel& model = signal_model_estimator_.get_model(); + const PriorSignalModel& prior_model = + signal_model_estimator_.get_prior_model(); + + // Width parameter in sigmoid map for prior model. + constexpr float kWidthPrior0 = 4.f; + // Width for pause region: lower range, so increase width in tanh map. + constexpr float kWidthPrior1 = 2.f * kWidthPrior0; + + // Average LRT feature: use larger width in tanh map for pause regions. + float width_prior = model.lrt < prior_model.lrt ? kWidthPrior1 : kWidthPrior0; + + // Compute indicator function: sigmoid map. + float indicator0 = + 0.5f * (tanh(width_prior * (model.lrt - prior_model.lrt)) + 1.f); + + // Spectral flatness feature: use larger width in tanh map for pause regions. + width_prior = model.spectral_flatness > prior_model.flatness_threshold + ? kWidthPrior1 + : kWidthPrior0; + + // Compute indicator function: sigmoid map. + float indicator1 = + 0.5f * (tanh(1.f * width_prior * + (prior_model.flatness_threshold - model.spectral_flatness)) + + 1.f); + + // For template spectrum-difference : use larger width in tanh map for pause + // regions. + width_prior = model.spectral_diff < prior_model.template_diff_threshold + ? kWidthPrior1 + : kWidthPrior0; + + // Compute indicator function: sigmoid map. + float indicator2 = + 0.5f * (tanh(width_prior * (model.spectral_diff - + prior_model.template_diff_threshold)) + + 1.f); + + // Combine the indicator function with the feature weights. + float ind_prior = prior_model.lrt_weighting * indicator0 + + prior_model.flatness_weighting * indicator1 + + prior_model.difference_weighting * indicator2; + + // Compute the prior probability. + prior_speech_prob_ += 0.1f * (ind_prior - prior_speech_prob_); + + // Make sure probabilities are within range: keep floor to 0.01. + prior_speech_prob_ = std::max(std::min(prior_speech_prob_, 1.f), 0.01f); + + // Final speech probability: combine prior model with LR factor:. + float gain_prior = + (1.f - prior_speech_prob_) / (prior_speech_prob_ + 0.0001f); + + std::array<float, kFftSizeBy2Plus1> inv_lrt; + ExpApproximationSignFlip(model.avg_log_lrt, inv_lrt); + for (size_t i = 0; i < kFftSizeBy2Plus1; ++i) { + speech_probability_[i] = 1.f / (1.f + gain_prior * inv_lrt[i]); + } +} + +} // namespace webrtc |