modules/audio_processing/transient/transient_suppressor.cc - mirrors/cros/chromiumos/third_party/webrtc-apm - Git at Google

 /*
  *  Copyright (c) 2013 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/transient/transient_suppressor.h"

 #include <math.h>
 #include <string.h>
 #include <cmath>
 #include <complex>
 #include <deque>
 #include <set>

 #include "common_audio/include/audio_util.h"
 #include "common_audio/signal_processing/include/signal_processing_library.h"
 #include "common_audio/third_party/fft4g/fft4g.h"
 #include "modules/audio_processing/ns/windows_private.h"
 #include "modules/audio_processing/transient/common.h"
 #include "modules/audio_processing/transient/transient_detector.h"
 #include "rtc_base/checks.h"
 #include "rtc_base/logging.h"

 namespace webrtc {

 static const float kMeanIIRCoefficient = 0.5f;
 static const float kVoiceThreshold = 0.02f;

 // TODO(aluebs): Check if these values work also for 48kHz.
 static const size_t kMinVoiceBin = 3;
 static const size_t kMaxVoiceBin = 60;

 namespace {

 float ComplexMagnitude(float a, float b) {
   return std::abs(a) + std::abs(b);
 }

 }  // namespace

 TransientSuppressor::TransientSuppressor()
     : data_length_(0),
       detection_length_(0),
       analysis_length_(0),
       buffer_delay_(0),
       complex_analysis_length_(0),
       num_channels_(0),
       window_(NULL),
       detector_smoothed_(0.f),
       keypress_counter_(0),
       chunks_since_keypress_(0),
       detection_enabled_(false),
       suppression_enabled_(false),
       use_hard_restoration_(false),
       chunks_since_voice_change_(0),
       seed_(182),
       using_reference_(false) {}

 TransientSuppressor::~TransientSuppressor() {}

 int TransientSuppressor::Initialize(int sample_rate_hz,
                                     int detection_rate_hz,
                                     int num_channels) {
   switch (sample_rate_hz) {
     case ts::kSampleRate8kHz:
       analysis_length_ = 128u;
       window_ = kBlocks80w128;
       break;
     case ts::kSampleRate16kHz:
       analysis_length_ = 256u;
       window_ = kBlocks160w256;
       break;
     case ts::kSampleRate32kHz:
       analysis_length_ = 512u;
       window_ = kBlocks320w512;
       break;
     case ts::kSampleRate48kHz:
       analysis_length_ = 1024u;
       window_ = kBlocks480w1024;
       break;
     default:
       return -1;
   }
   if (detection_rate_hz != ts::kSampleRate8kHz &&
       detection_rate_hz != ts::kSampleRate16kHz &&
       detection_rate_hz != ts::kSampleRate32kHz &&
       detection_rate_hz != ts::kSampleRate48kHz) {
     return -1;
   }
   if (num_channels <= 0) {
     return -1;
   }

   detector_.reset(new TransientDetector(detection_rate_hz));
   data_length_ = sample_rate_hz * ts::kChunkSizeMs / 1000;
   if (data_length_ > analysis_length_) {
     RTC_NOTREACHED();
     return -1;
   }
   buffer_delay_ = analysis_length_ - data_length_;

   complex_analysis_length_ = analysis_length_ / 2 + 1;
   RTC_DCHECK_GE(complex_analysis_length_, kMaxVoiceBin);
   num_channels_ = num_channels;
   in_buffer_.reset(new float[analysis_length_ * num_channels_]);
   memset(in_buffer_.get(), 0,
          analysis_length_ * num_channels_ * sizeof(in_buffer_[0]));
   detection_length_ = detection_rate_hz * ts::kChunkSizeMs / 1000;
   detection_buffer_.reset(new float[detection_length_]);
   memset(detection_buffer_.get(), 0,
          detection_length_ * sizeof(detection_buffer_[0]));
   out_buffer_.reset(new float[analysis_length_ * num_channels_]);
   memset(out_buffer_.get(), 0,
          analysis_length_ * num_channels_ * sizeof(out_buffer_[0]));
   // ip[0] must be zero to trigger initialization using rdft().
   size_t ip_length = 2 + sqrtf(analysis_length_);
   ip_.reset(new size_t[ip_length]());
   memset(ip_.get(), 0, ip_length * sizeof(ip_[0]));
   wfft_.reset(new float[complex_analysis_length_ - 1]);
   memset(wfft_.get(), 0, (complex_analysis_length_ - 1) * sizeof(wfft_[0]));
   spectral_mean_.reset(new float[complex_analysis_length_ * num_channels_]);
   memset(spectral_mean_.get(), 0,
          complex_analysis_length_ * num_channels_ * sizeof(spectral_mean_[0]));
   fft_buffer_.reset(new float[analysis_length_ + 2]);
   memset(fft_buffer_.get(), 0, (analysis_length_ + 2) * sizeof(fft_buffer_[0]));
   magnitudes_.reset(new float[complex_analysis_length_]);
   memset(magnitudes_.get(), 0,
          complex_analysis_length_ * sizeof(magnitudes_[0]));
   mean_factor_.reset(new float[complex_analysis_length_]);

   static const float kFactorHeight = 10.f;
   static const float kLowSlope = 1.f;
   static const float kHighSlope = 0.3f;
   for (size_t i = 0; i < complex_analysis_length_; ++i) {
     mean_factor_[i] =
         kFactorHeight /
             (1.f + exp(kLowSlope * static_cast<int>(i - kMinVoiceBin))) +
         kFactorHeight /
             (1.f + exp(kHighSlope * static_cast<int>(kMaxVoiceBin - i)));
   }
   detector_smoothed_ = 0.f;
   keypress_counter_ = 0;
   chunks_since_keypress_ = 0;
   detection_enabled_ = false;
   suppression_enabled_ = false;
   use_hard_restoration_ = false;
   chunks_since_voice_change_ = 0;
   seed_ = 182;
   using_reference_ = false;
   return 0;
 }

 int TransientSuppressor::Suppress(float* data,
                                   size_t data_length,
                                   int num_channels,
                                   const float* detection_data,
                                   size_t detection_length,
                                   const float* reference_data,
                                   size_t reference_length,
                                   float voice_probability,
                                   bool key_pressed) {
   if (!data || data_length != data_length_ || num_channels != num_channels_ ||
       detection_length != detection_length_ || voice_probability < 0 ||
       voice_probability > 1) {
     return -1;
   }

   UpdateKeypress(key_pressed);
   UpdateBuffers(data);

   int result = 0;
   if (detection_enabled_) {
     UpdateRestoration(voice_probability);

     if (!detection_data) {
       // Use the input data  of the first channel if special detection data is
       // not supplied.
       detection_data = &in_buffer_[buffer_delay_];
     }

     float detector_result = detector_->Detect(detection_data, detection_length,
                                               reference_data, reference_length);
     if (detector_result < 0) {
       return -1;
     }

     using_reference_ = detector_->using_reference();

     // |detector_smoothed_| follows the |detector_result| when this last one is
     // increasing, but has an exponential decaying tail to be able to suppress
     // the ringing of keyclicks.
     float smooth_factor = using_reference_ ? 0.6 : 0.1;
     detector_smoothed_ = detector_result >= detector_smoothed_
                              ? detector_result
                              : smooth_factor * detector_smoothed_ +
                                    (1 - smooth_factor) * detector_result;

     for (int i = 0; i < num_channels_; ++i) {
       Suppress(&in_buffer_[i * analysis_length_],
                &spectral_mean_[i * complex_analysis_length_],
                &out_buffer_[i * analysis_length_]);
     }
   }

   // If the suppression isn't enabled, we use the in buffer to delay the signal
   // appropriately. This also gives time for the out buffer to be refreshed with
   // new data between detection and suppression getting enabled.
   for (int i = 0; i < num_channels_; ++i) {
     memcpy(&data[i * data_length_],
            suppression_enabled_ ? &out_buffer_[i * analysis_length_]
                                 : &in_buffer_[i * analysis_length_],
            data_length_ * sizeof(*data));
   }
   return result;
 }

 // This should only be called when detection is enabled. UpdateBuffers() must
 // have been called. At return, |out_buffer_| will be filled with the
 // processed output.
 void TransientSuppressor::Suppress(float* in_ptr,
                                    float* spectral_mean,
                                    float* out_ptr) {
   // Go to frequency domain.
   for (size_t i = 0; i < analysis_length_; ++i) {
     // TODO(aluebs): Rename windows
     fft_buffer_[i] = in_ptr[i] * window_[i];
   }

   WebRtc_rdft(analysis_length_, 1, fft_buffer_.get(), ip_.get(), wfft_.get());

   // Since WebRtc_rdft puts R[n/2] in fft_buffer_[1], we move it to the end
   // for convenience.
   fft_buffer_[analysis_length_] = fft_buffer_[1];
   fft_buffer_[analysis_length_ + 1] = 0.f;
   fft_buffer_[1] = 0.f;

   for (size_t i = 0; i < complex_analysis_length_; ++i) {
     magnitudes_[i] =
         ComplexMagnitude(fft_buffer_[i * 2], fft_buffer_[i * 2 + 1]);
   }
   // Restore audio if necessary.
   if (suppression_enabled_) {
     if (use_hard_restoration_) {
       HardRestoration(spectral_mean);
     } else {
       SoftRestoration(spectral_mean);
     }
   }

   // Update the spectral mean.
   for (size_t i = 0; i < complex_analysis_length_; ++i) {
     spectral_mean[i] = (1 - kMeanIIRCoefficient) * spectral_mean[i] +
                        kMeanIIRCoefficient * magnitudes_[i];
   }

   // Back to time domain.
   // Put R[n/2] back in fft_buffer_[1].
   fft_buffer_[1] = fft_buffer_[analysis_length_];

   WebRtc_rdft(analysis_length_, -1, fft_buffer_.get(), ip_.get(), wfft_.get());
   const float fft_scaling = 2.f / analysis_length_;

   for (size_t i = 0; i < analysis_length_; ++i) {
     out_ptr[i] += fft_buffer_[i] * window_[i] * fft_scaling;
   }
 }

 void TransientSuppressor::UpdateKeypress(bool key_pressed) {
   const int kKeypressPenalty = 1000 / ts::kChunkSizeMs;
   const int kIsTypingThreshold = 1000 / ts::kChunkSizeMs;
   const int kChunksUntilNotTyping = 4000 / ts::kChunkSizeMs;  // 4 seconds.

   if (key_pressed) {
     keypress_counter_ += kKeypressPenalty;
     chunks_since_keypress_ = 0;
     detection_enabled_ = true;
   }
   keypress_counter_ = std::max(0, keypress_counter_ - 1);

   if (keypress_counter_ > kIsTypingThreshold) {
     if (!suppression_enabled_) {
       RTC_LOG(LS_INFO) << "[ts] Transient suppression is now enabled.";
     }
     suppression_enabled_ = true;
     keypress_counter_ = 0;
   }

   if (detection_enabled_ && ++chunks_since_keypress_ > kChunksUntilNotTyping) {
     if (suppression_enabled_) {
       RTC_LOG(LS_INFO) << "[ts] Transient suppression is now disabled.";
     }
     detection_enabled_ = false;
     suppression_enabled_ = false;
     keypress_counter_ = 0;
   }
 }

 void TransientSuppressor::UpdateRestoration(float voice_probability) {
   const int kHardRestorationOffsetDelay = 3;
   const int kHardRestorationOnsetDelay = 80;

   bool not_voiced = voice_probability < kVoiceThreshold;

   if (not_voiced == use_hard_restoration_) {
     chunks_since_voice_change_ = 0;
   } else {
     ++chunks_since_voice_change_;

     if ((use_hard_restoration_ &&
          chunks_since_voice_change_ > kHardRestorationOffsetDelay) ||
         (!use_hard_restoration_ &&
          chunks_since_voice_change_ > kHardRestorationOnsetDelay)) {
       use_hard_restoration_ = not_voiced;
       chunks_since_voice_change_ = 0;
     }
   }
 }

 // Shift buffers to make way for new data. Must be called after
 // |detection_enabled_| is updated by UpdateKeypress().
 void TransientSuppressor::UpdateBuffers(float* data) {
   // TODO(aluebs): Change to ring buffer.
   memmove(in_buffer_.get(), &in_buffer_[data_length_],
           (buffer_delay_ + (num_channels_ - 1) * analysis_length_) *
               sizeof(in_buffer_[0]));
   // Copy new chunk to buffer.
   for (int i = 0; i < num_channels_; ++i) {
     memcpy(&in_buffer_[buffer_delay_ + i * analysis_length_],
            &data[i * data_length_], data_length_ * sizeof(*data));
   }
   if (detection_enabled_) {
     // Shift previous chunk in out buffer.
     memmove(out_buffer_.get(), &out_buffer_[data_length_],
             (buffer_delay_ + (num_channels_ - 1) * analysis_length_) *
                 sizeof(out_buffer_[0]));
     // Initialize new chunk in out buffer.
     for (int i = 0; i < num_channels_; ++i) {
       memset(&out_buffer_[buffer_delay_ + i * analysis_length_], 0,
              data_length_ * sizeof(out_buffer_[0]));
     }
   }
 }

 // Restores the unvoiced signal if a click is present.
 // Attenuates by a certain factor every peak in the |fft_buffer_| that exceeds
 // the spectral mean. The attenuation depends on |detector_smoothed_|.
 // If a restoration takes place, the |magnitudes_| are updated to the new value.
 void TransientSuppressor::HardRestoration(float* spectral_mean) {
   const float detector_result =
       1.f - pow(1.f - detector_smoothed_, using_reference_ ? 200.f : 50.f);
   // To restore, we get the peaks in the spectrum. If higher than the previous
   // spectral mean we adjust them.
   for (size_t i = 0; i < complex_analysis_length_; ++i) {
     if (magnitudes_[i] > spectral_mean[i] && magnitudes_[i] > 0) {
       // RandU() generates values on [0, int16::max()]
       const float phase = 2 * ts::kPi * WebRtcSpl_RandU(&seed_) /
                           std::numeric_limits<int16_t>::max();
       const float scaled_mean = detector_result * spectral_mean[i];

       fft_buffer_[i * 2] = (1 - detector_result) * fft_buffer_[i * 2] +
                            scaled_mean * cosf(phase);
       fft_buffer_[i * 2 + 1] = (1 - detector_result) * fft_buffer_[i * 2 + 1] +
                                scaled_mean * sinf(phase);
       magnitudes_[i] = magnitudes_[i] -
                        detector_result * (magnitudes_[i] - spectral_mean[i]);
     }
   }
 }

 // Restores the voiced signal if a click is present.
 // Attenuates by a certain factor every peak in the |fft_buffer_| that exceeds
 // the spectral mean and that is lower than some function of the current block
 // frequency mean. The attenuation depends on |detector_smoothed_|.
 // If a restoration takes place, the |magnitudes_| are updated to the new value.
 void TransientSuppressor::SoftRestoration(float* spectral_mean) {
   // Get the spectral magnitude mean of the current block.
   float block_frequency_mean = 0;
   for (size_t i = kMinVoiceBin; i < kMaxVoiceBin; ++i) {
     block_frequency_mean += magnitudes_[i];
   }
   block_frequency_mean /= (kMaxVoiceBin - kMinVoiceBin);

   // To restore, we get the peaks in the spectrum. If higher than the
   // previous spectral mean and lower than a factor of the block mean
   // we adjust them. The factor is a double sigmoid that has a minimum in the
   // voice frequency range (300Hz - 3kHz).
   for (size_t i = 0; i < complex_analysis_length_; ++i) {
     if (magnitudes_[i] > spectral_mean[i] && magnitudes_[i] > 0 &&
         (using_reference_ ||
          magnitudes_[i] < block_frequency_mean * mean_factor_[i])) {
       const float new_magnitude =
           magnitudes_[i] -
           detector_smoothed_ * (magnitudes_[i] - spectral_mean[i]);
       const float magnitude_ratio = new_magnitude / magnitudes_[i];

       fft_buffer_[i * 2] *= magnitude_ratio;
       fft_buffer_[i * 2 + 1] *= magnitude_ratio;
       magnitudes_[i] = new_magnitude;
     }
   }
 }

 }  // namespace webrtc
	/*
	* Copyright (c) 2013 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/transient/transient_suppressor.h"

	#include <math.h>
	#include <string.h>
	#include <cmath>
	#include <complex>
	#include <deque>
	#include <set>

	#include "common_audio/include/audio_util.h"
	#include "common_audio/signal_processing/include/signal_processing_library.h"
	#include "common_audio/third_party/fft4g/fft4g.h"
	#include "modules/audio_processing/ns/windows_private.h"
	#include "modules/audio_processing/transient/common.h"
	#include "modules/audio_processing/transient/transient_detector.h"
	#include "rtc_base/checks.h"
	#include "rtc_base/logging.h"

	namespace webrtc {

	static const float kMeanIIRCoefficient = 0.5f;
	static const float kVoiceThreshold = 0.02f;

	// TODO(aluebs): Check if these values work also for 48kHz.
	static const size_t kMinVoiceBin = 3;
	static const size_t kMaxVoiceBin = 60;

	namespace {

	float ComplexMagnitude(float a, float b) {
	return std::abs(a) + std::abs(b);
	}

	} // namespace

	TransientSuppressor::TransientSuppressor()
	: data_length_(0),
	detection_length_(0),
	analysis_length_(0),
	buffer_delay_(0),
	complex_analysis_length_(0),
	num_channels_(0),
	window_(NULL),
	detector_smoothed_(0.f),
	keypress_counter_(0),
	chunks_since_keypress_(0),
	detection_enabled_(false),
	suppression_enabled_(false),
	use_hard_restoration_(false),
	chunks_since_voice_change_(0),
	seed_(182),
	using_reference_(false) {}

	TransientSuppressor::~TransientSuppressor() {}

	int TransientSuppressor::Initialize(int sample_rate_hz,
	int detection_rate_hz,
	int num_channels) {
	switch (sample_rate_hz) {
	case ts::kSampleRate8kHz:
	analysis_length_ = 128u;
	window_ = kBlocks80w128;
	break;
	case ts::kSampleRate16kHz:
	analysis_length_ = 256u;
	window_ = kBlocks160w256;
	break;
	case ts::kSampleRate32kHz:
	analysis_length_ = 512u;
	window_ = kBlocks320w512;
	break;
	case ts::kSampleRate48kHz:
	analysis_length_ = 1024u;
	window_ = kBlocks480w1024;
	break;
	default:
	return -1;
	}
	if (detection_rate_hz != ts::kSampleRate8kHz &&
	detection_rate_hz != ts::kSampleRate16kHz &&
	detection_rate_hz != ts::kSampleRate32kHz &&
	detection_rate_hz != ts::kSampleRate48kHz) {
	return -1;
	}
	if (num_channels <= 0) {
	return -1;
	}

	detector_.reset(new TransientDetector(detection_rate_hz));
	data_length_ = sample_rate_hz * ts::kChunkSizeMs / 1000;
	if (data_length_ > analysis_length_) {
	RTC_NOTREACHED();
	return -1;
	}
	buffer_delay_ = analysis_length_ - data_length_;

	complex_analysis_length_ = analysis_length_ / 2 + 1;
	RTC_DCHECK_GE(complex_analysis_length_, kMaxVoiceBin);
	num_channels_ = num_channels;
	in_buffer_.reset(new float[analysis_length_ * num_channels_]);
	memset(in_buffer_.get(), 0,
	analysis_length_ * num_channels_ * sizeof(in_buffer_[0]));
	detection_length_ = detection_rate_hz * ts::kChunkSizeMs / 1000;
	detection_buffer_.reset(new float[detection_length_]);
	memset(detection_buffer_.get(), 0,
	detection_length_ * sizeof(detection_buffer_[0]));
	out_buffer_.reset(new float[analysis_length_ * num_channels_]);
	memset(out_buffer_.get(), 0,
	analysis_length_ * num_channels_ * sizeof(out_buffer_[0]));
	// ip[0] must be zero to trigger initialization using rdft().
	size_t ip_length = 2 + sqrtf(analysis_length_);
	ip_.reset(new size_t[ip_length]());
	memset(ip_.get(), 0, ip_length * sizeof(ip_[0]));
	wfft_.reset(new float[complex_analysis_length_ - 1]);
	memset(wfft_.get(), 0, (complex_analysis_length_ - 1) * sizeof(wfft_[0]));
	spectral_mean_.reset(new float[complex_analysis_length_ * num_channels_]);
	memset(spectral_mean_.get(), 0,
	complex_analysis_length_ * num_channels_ * sizeof(spectral_mean_[0]));
	fft_buffer_.reset(new float[analysis_length_ + 2]);
	memset(fft_buffer_.get(), 0, (analysis_length_ + 2) * sizeof(fft_buffer_[0]));
	magnitudes_.reset(new float[complex_analysis_length_]);
	memset(magnitudes_.get(), 0,
	complex_analysis_length_ * sizeof(magnitudes_[0]));
	mean_factor_.reset(new float[complex_analysis_length_]);

	static const float kFactorHeight = 10.f;
	static const float kLowSlope = 1.f;
	static const float kHighSlope = 0.3f;
	for (size_t i = 0; i < complex_analysis_length_; ++i) {
	mean_factor_[i] =
	kFactorHeight /
	(1.f + exp(kLowSlope * static_cast<int>(i - kMinVoiceBin))) +
	kFactorHeight /
	(1.f + exp(kHighSlope * static_cast<int>(kMaxVoiceBin - i)));
	}
	detector_smoothed_ = 0.f;
	keypress_counter_ = 0;
	chunks_since_keypress_ = 0;
	detection_enabled_ = false;
	suppression_enabled_ = false;
	use_hard_restoration_ = false;
	chunks_since_voice_change_ = 0;
	seed_ = 182;
	using_reference_ = false;
	return 0;
	}

	int TransientSuppressor::Suppress(float* data,
	size_t data_length,
	int num_channels,
	const float* detection_data,
	size_t detection_length,
	const float* reference_data,
	size_t reference_length,
	float voice_probability,
	bool key_pressed) {
	if (!data \|\| data_length != data_length_ \|\| num_channels != num_channels_ \|\|
	detection_length != detection_length_ \|\| voice_probability < 0 \|\|
	voice_probability > 1) {
	return -1;
	}

	UpdateKeypress(key_pressed);
	UpdateBuffers(data);

	int result = 0;
	if (detection_enabled_) {
	UpdateRestoration(voice_probability);

	if (!detection_data) {
	// Use the input data of the first channel if special detection data is
	// not supplied.
	detection_data = &in_buffer_[buffer_delay_];
	}

	float detector_result = detector_->Detect(detection_data, detection_length,
	reference_data, reference_length);
	if (detector_result < 0) {
	return -1;
	}

	using_reference_ = detector_->using_reference();

	// \|detector_smoothed_\| follows the \|detector_result\| when this last one is
	// increasing, but has an exponential decaying tail to be able to suppress
	// the ringing of keyclicks.
	float smooth_factor = using_reference_ ? 0.6 : 0.1;
	detector_smoothed_ = detector_result >= detector_smoothed_
	? detector_result
	: smooth_factor * detector_smoothed_ +
	(1 - smooth_factor) * detector_result;

	for (int i = 0; i < num_channels_; ++i) {
	Suppress(&in_buffer_[i * analysis_length_],
	&spectral_mean_[i * complex_analysis_length_],
	&out_buffer_[i * analysis_length_]);
	}
	}

	// If the suppression isn't enabled, we use the in buffer to delay the signal
	// appropriately. This also gives time for the out buffer to be refreshed with
	// new data between detection and suppression getting enabled.
	for (int i = 0; i < num_channels_; ++i) {
	memcpy(&data[i * data_length_],
	suppression_enabled_ ? &out_buffer_[i * analysis_length_]
	: &in_buffer_[i * analysis_length_],
	data_length_ * sizeof(*data));
	}
	return result;
	}

	// This should only be called when detection is enabled. UpdateBuffers() must
	// have been called. At return, \|out_buffer_\| will be filled with the
	// processed output.
	void TransientSuppressor::Suppress(float* in_ptr,
	float* spectral_mean,
	float* out_ptr) {
	// Go to frequency domain.
	for (size_t i = 0; i < analysis_length_; ++i) {
	// TODO(aluebs): Rename windows
	fft_buffer_[i] = in_ptr[i] * window_[i];
	}

	WebRtc_rdft(analysis_length_, 1, fft_buffer_.get(), ip_.get(), wfft_.get());

	// Since WebRtc_rdft puts R[n/2] in fft_buffer_[1], we move it to the end
	// for convenience.
	fft_buffer_[analysis_length_] = fft_buffer_[1];
	fft_buffer_[analysis_length_ + 1] = 0.f;
	fft_buffer_[1] = 0.f;

	for (size_t i = 0; i < complex_analysis_length_; ++i) {
	magnitudes_[i] =
	ComplexMagnitude(fft_buffer_[i * 2], fft_buffer_[i * 2 + 1]);
	}
	// Restore audio if necessary.
	if (suppression_enabled_) {
	if (use_hard_restoration_) {
	HardRestoration(spectral_mean);
	} else {
	SoftRestoration(spectral_mean);
	}
	}

	// Update the spectral mean.
	for (size_t i = 0; i < complex_analysis_length_; ++i) {
	spectral_mean[i] = (1 - kMeanIIRCoefficient) * spectral_mean[i] +
	kMeanIIRCoefficient * magnitudes_[i];
	}

	// Back to time domain.
	// Put R[n/2] back in fft_buffer_[1].
	fft_buffer_[1] = fft_buffer_[analysis_length_];

	WebRtc_rdft(analysis_length_, -1, fft_buffer_.get(), ip_.get(), wfft_.get());
	const float fft_scaling = 2.f / analysis_length_;

	for (size_t i = 0; i < analysis_length_; ++i) {
	out_ptr[i] += fft_buffer_[i] * window_[i] * fft_scaling;
	}
	}

	void TransientSuppressor::UpdateKeypress(bool key_pressed) {
	const int kKeypressPenalty = 1000 / ts::kChunkSizeMs;
	const int kIsTypingThreshold = 1000 / ts::kChunkSizeMs;
	const int kChunksUntilNotTyping = 4000 / ts::kChunkSizeMs; // 4 seconds.

	if (key_pressed) {
	keypress_counter_ += kKeypressPenalty;
	chunks_since_keypress_ = 0;
	detection_enabled_ = true;
	}
	keypress_counter_ = std::max(0, keypress_counter_ - 1);

	if (keypress_counter_ > kIsTypingThreshold) {
	if (!suppression_enabled_) {
	RTC_LOG(LS_INFO) << "[ts] Transient suppression is now enabled.";
	}
	suppression_enabled_ = true;
	keypress_counter_ = 0;
	}

	if (detection_enabled_ && ++chunks_since_keypress_ > kChunksUntilNotTyping) {
	if (suppression_enabled_) {
	RTC_LOG(LS_INFO) << "[ts] Transient suppression is now disabled.";
	}
	detection_enabled_ = false;
	suppression_enabled_ = false;
	keypress_counter_ = 0;
	}
	}

	void TransientSuppressor::UpdateRestoration(float voice_probability) {
	const int kHardRestorationOffsetDelay = 3;
	const int kHardRestorationOnsetDelay = 80;

	bool not_voiced = voice_probability < kVoiceThreshold;

	if (not_voiced == use_hard_restoration_) {
	chunks_since_voice_change_ = 0;
	} else {
	++chunks_since_voice_change_;

	if ((use_hard_restoration_ &&
	chunks_since_voice_change_ > kHardRestorationOffsetDelay) \|\|
	(!use_hard_restoration_ &&
	chunks_since_voice_change_ > kHardRestorationOnsetDelay)) {
	use_hard_restoration_ = not_voiced;
	chunks_since_voice_change_ = 0;
	}
	}
	}

	// Shift buffers to make way for new data. Must be called after
	// \|detection_enabled_\| is updated by UpdateKeypress().
	void TransientSuppressor::UpdateBuffers(float* data) {
	// TODO(aluebs): Change to ring buffer.
	memmove(in_buffer_.get(), &in_buffer_[data_length_],
	(buffer_delay_ + (num_channels_ - 1) * analysis_length_) *
	sizeof(in_buffer_[0]));
	// Copy new chunk to buffer.
	for (int i = 0; i < num_channels_; ++i) {
	memcpy(&in_buffer_[buffer_delay_ + i * analysis_length_],
	&data[i * data_length_], data_length_ * sizeof(*data));
	}
	if (detection_enabled_) {
	// Shift previous chunk in out buffer.
	memmove(out_buffer_.get(), &out_buffer_[data_length_],
	(buffer_delay_ + (num_channels_ - 1) * analysis_length_) *
	sizeof(out_buffer_[0]));
	// Initialize new chunk in out buffer.
	for (int i = 0; i < num_channels_; ++i) {
	memset(&out_buffer_[buffer_delay_ + i * analysis_length_], 0,
	data_length_ * sizeof(out_buffer_[0]));
	}
	}
	}

	// Restores the unvoiced signal if a click is present.
	// Attenuates by a certain factor every peak in the \|fft_buffer_\| that exceeds
	// the spectral mean. The attenuation depends on \|detector_smoothed_\|.
	// If a restoration takes place, the \|magnitudes_\| are updated to the new value.
	void TransientSuppressor::HardRestoration(float* spectral_mean) {
	const float detector_result =
	1.f - pow(1.f - detector_smoothed_, using_reference_ ? 200.f : 50.f);
	// To restore, we get the peaks in the spectrum. If higher than the previous
	// spectral mean we adjust them.
	for (size_t i = 0; i < complex_analysis_length_; ++i) {
	if (magnitudes_[i] > spectral_mean[i] && magnitudes_[i] > 0) {
	// RandU() generates values on [0, int16::max()]
	const float phase = 2 * ts::kPi * WebRtcSpl_RandU(&seed_) /
	std::numeric_limits<int16_t>::max();
	const float scaled_mean = detector_result * spectral_mean[i];

	fft_buffer_[i * 2] = (1 - detector_result) * fft_buffer_[i * 2] +
	scaled_mean * cosf(phase);
	fft_buffer_[i * 2 + 1] = (1 - detector_result) * fft_buffer_[i * 2 + 1] +
	scaled_mean * sinf(phase);
	magnitudes_[i] = magnitudes_[i] -
	detector_result * (magnitudes_[i] - spectral_mean[i]);
	}
	}
	}

	// Restores the voiced signal if a click is present.
	// Attenuates by a certain factor every peak in the \|fft_buffer_\| that exceeds
	// the spectral mean and that is lower than some function of the current block
	// frequency mean. The attenuation depends on \|detector_smoothed_\|.
	// If a restoration takes place, the \|magnitudes_\| are updated to the new value.
	void TransientSuppressor::SoftRestoration(float* spectral_mean) {
	// Get the spectral magnitude mean of the current block.
	float block_frequency_mean = 0;
	for (size_t i = kMinVoiceBin; i < kMaxVoiceBin; ++i) {
	block_frequency_mean += magnitudes_[i];
	}
	block_frequency_mean /= (kMaxVoiceBin - kMinVoiceBin);

	// To restore, we get the peaks in the spectrum. If higher than the
	// previous spectral mean and lower than a factor of the block mean
	// we adjust them. The factor is a double sigmoid that has a minimum in the
	// voice frequency range (300Hz - 3kHz).
	for (size_t i = 0; i < complex_analysis_length_; ++i) {
	if (magnitudes_[i] > spectral_mean[i] && magnitudes_[i] > 0 &&
	(using_reference_ \|\|
	magnitudes_[i] < block_frequency_mean * mean_factor_[i])) {
	const float new_magnitude =
	magnitudes_[i] -
	detector_smoothed_ * (magnitudes_[i] - spectral_mean[i]);
	const float magnitude_ratio = new_magnitude / magnitudes_[i];

	fft_buffer_[i * 2] *= magnitude_ratio;
	fft_buffer_[i * 2 + 1] *= magnitude_ratio;
	magnitudes_[i] = new_magnitude;
	}
	}
	}

	} // namespace webrtc