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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.
*/
#include <math.h>
#include <stdio.h>
#include <stdlib.h>
#include <algorithm>
#include <memory>
#include "gflags/gflags.h"
#include "testing/gtest/include/gtest/gtest.h"
#include "webrtc/modules/audio_processing/agc/agc.h"
#include "webrtc/modules/audio_processing/agc/loudness_histogram.h"
#include "webrtc/modules/audio_processing/agc/utility.h"
#include "webrtc/modules/audio_processing/vad/vad_audio_proc.h"
#include "webrtc/modules/audio_processing/vad/common.h"
#include "webrtc/modules/audio_processing/vad/pitch_based_vad.h"
#include "webrtc/modules/audio_processing/vad/standalone_vad.h"
#include "webrtc/modules/include/module_common_types.h"
static const int kAgcAnalWindowSamples = 100;
static const double kDefaultActivityThreshold = 0.3;
DEFINE_bool(standalone_vad, true, "enable stand-alone VAD");
DEFINE_string(true_vad, "", "name of a file containing true VAD in 'int'"
" format");
DEFINE_string(video_vad, "", "name of a file containing video VAD (activity"
" probabilities) in double format. One activity per 10ms is"
" required. If no file is given the video information is not"
" incorporated. Negative activity is interpreted as video is"
" not adapted and the statistics are not computed during"
" the learning phase. Note that the negative video activities"
" are ONLY allowed at the beginning.");
DEFINE_string(result, "", "name of a file to write the results. The results"
" will be appended to the end of the file. This is optional.");
DEFINE_string(audio_content, "", "name of a file where audio content is written"
" to, in double format.");
DEFINE_double(activity_threshold, kDefaultActivityThreshold,
"Activity threshold");
namespace webrtc {
// TODO(turajs) A new CL will be committed soon where ExtractFeatures will
// notify the caller of "silence" input, instead of bailing out. We would not
// need the following function when such a change is made.
// Add some dither to quiet frames. This avoids the ExtractFeatures skip a
// silence frame. Otherwise true VAD would drift with respect to the audio.
// We only consider mono inputs.
static void DitherSilence(AudioFrame* frame) {
ASSERT_EQ(1u, frame->num_channels_);
const double kRmsSilence = 5;
const double sum_squared_silence = kRmsSilence * kRmsSilence *
frame->samples_per_channel_;
double sum_squared = 0;
for (size_t n = 0; n < frame->samples_per_channel_; n++)
sum_squared += frame->data_[n] * frame->data_[n];
if (sum_squared <= sum_squared_silence) {
for (size_t n = 0; n < frame->samples_per_channel_; n++)
frame->data_[n] = (rand() & 0xF) - 8; // NOLINT: ignore non-threadsafe.
}
}
class AgcStat {
public:
AgcStat()
: video_index_(0),
activity_threshold_(kDefaultActivityThreshold),
audio_content_(LoudnessHistogram::Create(kAgcAnalWindowSamples)),
audio_processing_(new VadAudioProc()),
vad_(new PitchBasedVad()),
standalone_vad_(StandaloneVad::Create()),
audio_content_fid_(NULL) {
for (size_t n = 0; n < kMaxNumFrames; n++)
video_vad_[n] = 0.5;
}
~AgcStat() {
if (audio_content_fid_ != NULL) {
fclose(audio_content_fid_);
}
}
void set_audio_content_file(FILE* audio_content_fid) {
audio_content_fid_ = audio_content_fid;
}
int AddAudio(const AudioFrame& frame, double p_video,
int* combined_vad) {
if (frame.num_channels_ != 1 ||
frame.samples_per_channel_ !=
kSampleRateHz / 100 ||
frame.sample_rate_hz_ != kSampleRateHz)
return -1;
video_vad_[video_index_++] = p_video;
AudioFeatures features;
audio_processing_->ExtractFeatures(
frame.data_, frame.samples_per_channel_, &features);
if (FLAGS_standalone_vad) {
standalone_vad_->AddAudio(frame.data_,
frame.samples_per_channel_);
}
if (features.num_frames > 0) {
double p[kMaxNumFrames] = {0.5, 0.5, 0.5, 0.5};
if (FLAGS_standalone_vad) {
standalone_vad_->GetActivity(p, kMaxNumFrames);
}
// TODO(turajs) combining and limiting are used in the source files as
// well they can be moved to utility.
// Combine Video and stand-alone VAD.
for (size_t n = 0; n < features.num_frames; n++) {
double p_active = p[n] * video_vad_[n];
double p_passive = (1 - p[n]) * (1 - video_vad_[n]);
p[n] = p_active / (p_active + p_passive);
// Limit probabilities.
p[n] = std::min(std::max(p[n], 0.01), 0.99);
}
if (vad_->VoicingProbability(features, p) < 0)
return -1;
for (size_t n = 0; n < features.num_frames; n++) {
audio_content_->Update(features.rms[n], p[n]);
double ac = audio_content_->AudioContent();
if (audio_content_fid_ != NULL) {
fwrite(&ac, sizeof(ac), 1, audio_content_fid_);
}
if (ac > kAgcAnalWindowSamples * activity_threshold_) {
combined_vad[n] = 1;
} else {
combined_vad[n] = 0;
}
}
video_index_ = 0;
}
return static_cast<int>(features.num_frames);
}
void Reset() {
audio_content_->Reset();
}
void SetActivityThreshold(double activity_threshold) {
activity_threshold_ = activity_threshold;
}
private:
int video_index_;
double activity_threshold_;
double video_vad_[kMaxNumFrames];
std::unique_ptr<LoudnessHistogram> audio_content_;
std::unique_ptr<VadAudioProc> audio_processing_;
std::unique_ptr<PitchBasedVad> vad_;
std::unique_ptr<StandaloneVad> standalone_vad_;
FILE* audio_content_fid_;
};
void void_main(int argc, char* argv[]) {
webrtc::AgcStat agc_stat;
FILE* pcm_fid = fopen(argv[1], "rb");
ASSERT_TRUE(pcm_fid != NULL) << "Cannot open PCM file " << argv[1];
if (argc < 2) {
fprintf(stderr, "\nNot Enough arguments\n");
}
FILE* true_vad_fid = NULL;
ASSERT_GT(FLAGS_true_vad.size(), 0u) << "Specify the file containing true "
"VADs using --true_vad flag.";
true_vad_fid = fopen(FLAGS_true_vad.c_str(), "rb");
ASSERT_TRUE(true_vad_fid != NULL) << "Cannot open the active list " <<
FLAGS_true_vad;
FILE* results_fid = NULL;
if (FLAGS_result.size() > 0) {
// True if this is the first time writing to this function and we add a
// header to the beginning of the file.
bool write_header;
// Open in the read mode. If it fails, the file doesn't exist and has to
// write a header for it. Otherwise no need to write a header.
results_fid = fopen(FLAGS_result.c_str(), "r");
if (results_fid == NULL) {
write_header = true;
} else {
fclose(results_fid);
write_header = false;
}
// Open in append mode.
results_fid = fopen(FLAGS_result.c_str(), "a");
ASSERT_TRUE(results_fid != NULL) << "Cannot open the file, " <<
FLAGS_result << ", to write the results.";
// Write the header if required.
if (write_header) {
fprintf(results_fid, "%% Total Active, Misdetection, "
"Total inactive, False Positive, On-sets, Missed segments, "
"Average response\n");
}
}
FILE* video_vad_fid = NULL;
if (FLAGS_video_vad.size() > 0) {
video_vad_fid = fopen(FLAGS_video_vad.c_str(), "rb");
ASSERT_TRUE(video_vad_fid != NULL) << "Cannot open the file, " <<
FLAGS_video_vad << " to read video-based VAD decisions.\n";
}
// AgsStat will be the owner of this file and will close it at its
// destructor.
FILE* audio_content_fid = NULL;
if (FLAGS_audio_content.size() > 0) {
audio_content_fid = fopen(FLAGS_audio_content.c_str(), "wb");
ASSERT_TRUE(audio_content_fid != NULL) << "Cannot open file, " <<
FLAGS_audio_content << " to write audio-content.\n";
agc_stat.set_audio_content_file(audio_content_fid);
}
webrtc::AudioFrame frame;
frame.num_channels_ = 1;
frame.sample_rate_hz_ = 16000;
frame.samples_per_channel_ = frame.sample_rate_hz_ / 100;
const size_t kSamplesToRead = frame.num_channels_ *
frame.samples_per_channel_;
agc_stat.SetActivityThreshold(FLAGS_activity_threshold);
int ret_val = 0;
int num_frames = 0;
int agc_vad[kMaxNumFrames];
uint8_t true_vad[kMaxNumFrames];
double p_video = 0.5;
int total_active = 0;
int total_passive = 0;
int total_false_positive = 0;
int total_missed_detection = 0;
int onset_adaptation = 0;
int num_onsets = 0;
bool onset = false;
uint8_t previous_true_vad = 0;
int num_not_adapted = 0;
size_t true_vad_index = 0;
bool in_false_positive_region = false;
int total_false_positive_duration = 0;
bool video_adapted = false;
while (kSamplesToRead == fread(frame.data_, sizeof(int16_t),
kSamplesToRead, pcm_fid)) {
assert(true_vad_index < kMaxNumFrames);
ASSERT_EQ(1u, fread(&true_vad[true_vad_index], sizeof(*true_vad), 1,
true_vad_fid))
<< "Size mismatch between True-VAD and the PCM file.\n";
if (video_vad_fid != NULL) {
ASSERT_EQ(1u, fread(&p_video, sizeof(p_video), 1, video_vad_fid)) <<
"Not enough video-based VAD probabilities.";
}
// Negative video activity indicates that the video-based VAD is not yet
// adapted. Disregards the learning phase in statistics.
if (p_video < 0) {
if (video_adapted) {
fprintf(stderr, "Negative video probabilities ONLY allowed at the "
"beginning of the sequence, not in the middle.\n");
exit(1);
}
continue;
} else {
video_adapted = true;
}
num_frames++;
uint8_t last_true_vad;
if (true_vad_index == 0) {
last_true_vad = previous_true_vad;
} else {
last_true_vad = true_vad[true_vad_index - 1];
}
if (last_true_vad == 1 && true_vad[true_vad_index] == 0) {
agc_stat.Reset();
}
true_vad_index++;
DitherSilence(&frame);
ret_val = agc_stat.AddAudio(frame, p_video, agc_vad);
ASSERT_GE(ret_val, 0);
if (ret_val > 0) {
ASSERT_EQ(true_vad_index, static_cast<size_t>(ret_val));
for (int n = 0; n < ret_val; n++) {
if (true_vad[n] == 1) {
total_active++;
if (previous_true_vad == 0) {
num_onsets++;
onset = true;
}
if (agc_vad[n] == 0) {
total_missed_detection++;
if (onset)
onset_adaptation++;
} else {
in_false_positive_region = false;
onset = false;
}
} else if (true_vad[n] == 0) {
// Check if |on_set| flag is still up. If so it means that we totally
// missed an active region
if (onset)
num_not_adapted++;
onset = false;
total_passive++;
if (agc_vad[n] == 1) {
total_false_positive++;
in_false_positive_region = true;
}
if (in_false_positive_region) {
total_false_positive_duration++;
}
} else {
ASSERT_TRUE(false) << "Invalid value for true-VAD.\n";
}
previous_true_vad = true_vad[n];
}
true_vad_index = 0;
}
}
if (results_fid != NULL) {
fprintf(results_fid, "%4d %4d %4d %4d %4d %4d %4.0f %4.0f\n",
total_active,
total_missed_detection,
total_passive,
total_false_positive,
num_onsets,
num_not_adapted,
static_cast<float>(onset_adaptation) / (num_onsets + 1e-12),
static_cast<float>(total_false_positive_duration) /
(total_passive + 1e-12));
}
fprintf(stdout, "%4d %4d %4d %4d %4d %4d %4.0f %4.0f\n",
total_active,
total_missed_detection,
total_passive,
total_false_positive,
num_onsets,
num_not_adapted,
static_cast<float>(onset_adaptation) / (num_onsets + 1e-12),
static_cast<float>(total_false_positive_duration) /
(total_passive + 1e-12));
fclose(true_vad_fid);
fclose(pcm_fid);
if (video_vad_fid != NULL) {
fclose(video_vad_fid);
}
if (results_fid != NULL) {
fclose(results_fid);
}
}
} // namespace webrtc
int main(int argc, char* argv[]) {
char kUsage[] =
"\nCompute the number of misdetected and false-positive frames. Not\n"
" that for each frame of audio (10 ms) there should be one true\n"
" activity. If any video-based activity is given, there should also be\n"
" one probability per frame.\n"
"\nUsage:\n\n"
"activity_metric input_pcm [options]\n"
"where 'input_pcm' is the input audio sampled at 16 kHz in 16 bits "
"format.\n\n";
google::SetUsageMessage(kUsage);
google::ParseCommandLineFlags(&argc, &argv, true);
webrtc::void_main(argc, argv);
return 0;
}