386 lines
13 KiB
C++
386 lines
13 KiB
C++
/*
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* Copyright (c) 2012 The WebRTC project authors. All Rights Reserved.
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*
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* Use of this source code is governed by a BSD-style license
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* that can be found in the LICENSE file in the root of the source
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* tree. An additional intellectual property rights grant can be found
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* in the file PATENTS. All contributing project authors may
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* be found in the AUTHORS file in the root of the source tree.
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*/
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#include <math.h>
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#include <stdio.h>
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#include <stdlib.h>
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#include <algorithm>
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#include <memory>
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#include "gflags/gflags.h"
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#include "testing/gtest/include/gtest/gtest.h"
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#include "webrtc/modules/audio_processing/agc/agc.h"
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#include "webrtc/modules/audio_processing/agc/loudness_histogram.h"
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#include "webrtc/modules/audio_processing/agc/utility.h"
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#include "webrtc/modules/audio_processing/vad/vad_audio_proc.h"
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#include "webrtc/modules/audio_processing/vad/common.h"
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#include "webrtc/modules/audio_processing/vad/pitch_based_vad.h"
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#include "webrtc/modules/audio_processing/vad/standalone_vad.h"
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#include "webrtc/modules/include/module_common_types.h"
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static const int kAgcAnalWindowSamples = 100;
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static const double kDefaultActivityThreshold = 0.3;
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DEFINE_bool(standalone_vad, true, "enable stand-alone VAD");
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DEFINE_string(true_vad, "", "name of a file containing true VAD in 'int'"
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" format");
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DEFINE_string(video_vad, "", "name of a file containing video VAD (activity"
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" probabilities) in double format. One activity per 10ms is"
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" required. If no file is given the video information is not"
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" incorporated. Negative activity is interpreted as video is"
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" not adapted and the statistics are not computed during"
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" the learning phase. Note that the negative video activities"
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" are ONLY allowed at the beginning.");
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DEFINE_string(result, "", "name of a file to write the results. The results"
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" will be appended to the end of the file. This is optional.");
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DEFINE_string(audio_content, "", "name of a file where audio content is written"
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" to, in double format.");
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DEFINE_double(activity_threshold, kDefaultActivityThreshold,
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"Activity threshold");
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namespace webrtc {
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// TODO(turajs) A new CL will be committed soon where ExtractFeatures will
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// notify the caller of "silence" input, instead of bailing out. We would not
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// need the following function when such a change is made.
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// Add some dither to quiet frames. This avoids the ExtractFeatures skip a
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// silence frame. Otherwise true VAD would drift with respect to the audio.
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// We only consider mono inputs.
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static void DitherSilence(AudioFrame* frame) {
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ASSERT_EQ(1u, frame->num_channels_);
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const double kRmsSilence = 5;
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const double sum_squared_silence = kRmsSilence * kRmsSilence *
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frame->samples_per_channel_;
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double sum_squared = 0;
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for (size_t n = 0; n < frame->samples_per_channel_; n++)
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sum_squared += frame->data_[n] * frame->data_[n];
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if (sum_squared <= sum_squared_silence) {
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for (size_t n = 0; n < frame->samples_per_channel_; n++)
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frame->data_[n] = (rand() & 0xF) - 8; // NOLINT: ignore non-threadsafe.
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}
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}
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class AgcStat {
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public:
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AgcStat()
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: video_index_(0),
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activity_threshold_(kDefaultActivityThreshold),
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audio_content_(LoudnessHistogram::Create(kAgcAnalWindowSamples)),
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audio_processing_(new VadAudioProc()),
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vad_(new PitchBasedVad()),
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standalone_vad_(StandaloneVad::Create()),
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audio_content_fid_(NULL) {
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for (size_t n = 0; n < kMaxNumFrames; n++)
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video_vad_[n] = 0.5;
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}
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~AgcStat() {
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if (audio_content_fid_ != NULL) {
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fclose(audio_content_fid_);
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}
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}
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void set_audio_content_file(FILE* audio_content_fid) {
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audio_content_fid_ = audio_content_fid;
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}
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int AddAudio(const AudioFrame& frame, double p_video,
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int* combined_vad) {
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if (frame.num_channels_ != 1 ||
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frame.samples_per_channel_ !=
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kSampleRateHz / 100 ||
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frame.sample_rate_hz_ != kSampleRateHz)
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return -1;
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video_vad_[video_index_++] = p_video;
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AudioFeatures features;
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audio_processing_->ExtractFeatures(
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frame.data_, frame.samples_per_channel_, &features);
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if (FLAGS_standalone_vad) {
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standalone_vad_->AddAudio(frame.data_,
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frame.samples_per_channel_);
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}
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if (features.num_frames > 0) {
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double p[kMaxNumFrames] = {0.5, 0.5, 0.5, 0.5};
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if (FLAGS_standalone_vad) {
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standalone_vad_->GetActivity(p, kMaxNumFrames);
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}
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// TODO(turajs) combining and limiting are used in the source files as
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// well they can be moved to utility.
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// Combine Video and stand-alone VAD.
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for (size_t n = 0; n < features.num_frames; n++) {
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double p_active = p[n] * video_vad_[n];
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double p_passive = (1 - p[n]) * (1 - video_vad_[n]);
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p[n] = p_active / (p_active + p_passive);
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// Limit probabilities.
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p[n] = std::min(std::max(p[n], 0.01), 0.99);
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}
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if (vad_->VoicingProbability(features, p) < 0)
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return -1;
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for (size_t n = 0; n < features.num_frames; n++) {
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audio_content_->Update(features.rms[n], p[n]);
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double ac = audio_content_->AudioContent();
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if (audio_content_fid_ != NULL) {
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fwrite(&ac, sizeof(ac), 1, audio_content_fid_);
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}
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if (ac > kAgcAnalWindowSamples * activity_threshold_) {
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combined_vad[n] = 1;
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} else {
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combined_vad[n] = 0;
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}
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}
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video_index_ = 0;
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}
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return static_cast<int>(features.num_frames);
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}
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void Reset() {
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audio_content_->Reset();
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}
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void SetActivityThreshold(double activity_threshold) {
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activity_threshold_ = activity_threshold;
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}
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private:
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int video_index_;
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double activity_threshold_;
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double video_vad_[kMaxNumFrames];
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std::unique_ptr<LoudnessHistogram> audio_content_;
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std::unique_ptr<VadAudioProc> audio_processing_;
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std::unique_ptr<PitchBasedVad> vad_;
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std::unique_ptr<StandaloneVad> standalone_vad_;
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FILE* audio_content_fid_;
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};
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void void_main(int argc, char* argv[]) {
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webrtc::AgcStat agc_stat;
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FILE* pcm_fid = fopen(argv[1], "rb");
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ASSERT_TRUE(pcm_fid != NULL) << "Cannot open PCM file " << argv[1];
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if (argc < 2) {
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fprintf(stderr, "\nNot Enough arguments\n");
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}
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FILE* true_vad_fid = NULL;
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ASSERT_GT(FLAGS_true_vad.size(), 0u) << "Specify the file containing true "
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"VADs using --true_vad flag.";
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true_vad_fid = fopen(FLAGS_true_vad.c_str(), "rb");
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ASSERT_TRUE(true_vad_fid != NULL) << "Cannot open the active list " <<
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FLAGS_true_vad;
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FILE* results_fid = NULL;
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if (FLAGS_result.size() > 0) {
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// True if this is the first time writing to this function and we add a
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// header to the beginning of the file.
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bool write_header;
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// Open in the read mode. If it fails, the file doesn't exist and has to
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// write a header for it. Otherwise no need to write a header.
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results_fid = fopen(FLAGS_result.c_str(), "r");
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if (results_fid == NULL) {
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write_header = true;
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} else {
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fclose(results_fid);
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write_header = false;
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}
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// Open in append mode.
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results_fid = fopen(FLAGS_result.c_str(), "a");
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ASSERT_TRUE(results_fid != NULL) << "Cannot open the file, " <<
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FLAGS_result << ", to write the results.";
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// Write the header if required.
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if (write_header) {
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fprintf(results_fid, "%% Total Active, Misdetection, "
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"Total inactive, False Positive, On-sets, Missed segments, "
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"Average response\n");
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}
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}
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FILE* video_vad_fid = NULL;
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if (FLAGS_video_vad.size() > 0) {
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video_vad_fid = fopen(FLAGS_video_vad.c_str(), "rb");
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ASSERT_TRUE(video_vad_fid != NULL) << "Cannot open the file, " <<
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FLAGS_video_vad << " to read video-based VAD decisions.\n";
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}
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// AgsStat will be the owner of this file and will close it at its
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// destructor.
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FILE* audio_content_fid = NULL;
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if (FLAGS_audio_content.size() > 0) {
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audio_content_fid = fopen(FLAGS_audio_content.c_str(), "wb");
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ASSERT_TRUE(audio_content_fid != NULL) << "Cannot open file, " <<
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FLAGS_audio_content << " to write audio-content.\n";
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agc_stat.set_audio_content_file(audio_content_fid);
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}
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webrtc::AudioFrame frame;
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frame.num_channels_ = 1;
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frame.sample_rate_hz_ = 16000;
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frame.samples_per_channel_ = frame.sample_rate_hz_ / 100;
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const size_t kSamplesToRead = frame.num_channels_ *
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frame.samples_per_channel_;
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agc_stat.SetActivityThreshold(FLAGS_activity_threshold);
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int ret_val = 0;
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int num_frames = 0;
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int agc_vad[kMaxNumFrames];
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uint8_t true_vad[kMaxNumFrames];
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double p_video = 0.5;
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int total_active = 0;
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int total_passive = 0;
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int total_false_positive = 0;
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int total_missed_detection = 0;
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int onset_adaptation = 0;
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int num_onsets = 0;
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bool onset = false;
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uint8_t previous_true_vad = 0;
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int num_not_adapted = 0;
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size_t true_vad_index = 0;
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bool in_false_positive_region = false;
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int total_false_positive_duration = 0;
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bool video_adapted = false;
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while (kSamplesToRead == fread(frame.data_, sizeof(int16_t),
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kSamplesToRead, pcm_fid)) {
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assert(true_vad_index < kMaxNumFrames);
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ASSERT_EQ(1u, fread(&true_vad[true_vad_index], sizeof(*true_vad), 1,
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true_vad_fid))
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<< "Size mismatch between True-VAD and the PCM file.\n";
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if (video_vad_fid != NULL) {
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ASSERT_EQ(1u, fread(&p_video, sizeof(p_video), 1, video_vad_fid)) <<
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"Not enough video-based VAD probabilities.";
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}
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// Negative video activity indicates that the video-based VAD is not yet
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// adapted. Disregards the learning phase in statistics.
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if (p_video < 0) {
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if (video_adapted) {
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fprintf(stderr, "Negative video probabilities ONLY allowed at the "
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"beginning of the sequence, not in the middle.\n");
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exit(1);
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}
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continue;
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} else {
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video_adapted = true;
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}
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num_frames++;
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uint8_t last_true_vad;
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if (true_vad_index == 0) {
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last_true_vad = previous_true_vad;
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} else {
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last_true_vad = true_vad[true_vad_index - 1];
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}
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if (last_true_vad == 1 && true_vad[true_vad_index] == 0) {
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agc_stat.Reset();
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}
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true_vad_index++;
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DitherSilence(&frame);
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ret_val = agc_stat.AddAudio(frame, p_video, agc_vad);
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ASSERT_GE(ret_val, 0);
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if (ret_val > 0) {
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ASSERT_EQ(true_vad_index, static_cast<size_t>(ret_val));
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for (int n = 0; n < ret_val; n++) {
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if (true_vad[n] == 1) {
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total_active++;
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if (previous_true_vad == 0) {
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num_onsets++;
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onset = true;
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}
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if (agc_vad[n] == 0) {
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total_missed_detection++;
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if (onset)
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onset_adaptation++;
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} else {
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in_false_positive_region = false;
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onset = false;
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}
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} else if (true_vad[n] == 0) {
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// Check if |on_set| flag is still up. If so it means that we totally
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// missed an active region
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if (onset)
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num_not_adapted++;
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onset = false;
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total_passive++;
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if (agc_vad[n] == 1) {
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total_false_positive++;
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in_false_positive_region = true;
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}
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if (in_false_positive_region) {
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total_false_positive_duration++;
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}
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} else {
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ASSERT_TRUE(false) << "Invalid value for true-VAD.\n";
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}
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previous_true_vad = true_vad[n];
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}
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true_vad_index = 0;
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}
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}
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if (results_fid != NULL) {
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fprintf(results_fid, "%4d %4d %4d %4d %4d %4d %4.0f %4.0f\n",
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total_active,
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total_missed_detection,
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total_passive,
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total_false_positive,
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num_onsets,
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num_not_adapted,
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static_cast<float>(onset_adaptation) / (num_onsets + 1e-12),
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static_cast<float>(total_false_positive_duration) /
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(total_passive + 1e-12));
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}
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fprintf(stdout, "%4d %4d %4d %4d %4d %4d %4.0f %4.0f\n",
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total_active,
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total_missed_detection,
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total_passive,
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total_false_positive,
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num_onsets,
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num_not_adapted,
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static_cast<float>(onset_adaptation) / (num_onsets + 1e-12),
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static_cast<float>(total_false_positive_duration) /
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(total_passive + 1e-12));
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fclose(true_vad_fid);
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fclose(pcm_fid);
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if (video_vad_fid != NULL) {
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fclose(video_vad_fid);
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}
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if (results_fid != NULL) {
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fclose(results_fid);
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}
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}
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} // namespace webrtc
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int main(int argc, char* argv[]) {
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char kUsage[] =
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"\nCompute the number of misdetected and false-positive frames. Not\n"
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" that for each frame of audio (10 ms) there should be one true\n"
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" activity. If any video-based activity is given, there should also be\n"
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" one probability per frame.\n"
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"\nUsage:\n\n"
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"activity_metric input_pcm [options]\n"
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"where 'input_pcm' is the input audio sampled at 16 kHz in 16 bits "
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"format.\n\n";
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google::SetUsageMessage(kUsage);
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google::ParseCommandLineFlags(&argc, &argv, true);
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webrtc::void_main(argc, argv);
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return 0;
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}
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