blob: f4ee17760e95753271ae40aca65475e635480c71 [file] [log] [blame]
/*
* Copyright (c) 2015 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 "webrtc/modules/audio_processing/vad/voice_activity_detector.h"
#include <algorithm>
#include <vector>
#include "testing/gtest/include/gtest/gtest.h"
#include "webrtc/test/testsupport/fileutils.h"
namespace webrtc {
namespace {
const int kStartTimeSec = 16;
const float kMeanSpeechProbability = 0.3f;
const float kMaxNoiseProbability = 0.1f;
const size_t kNumChunks = 300u;
const size_t kNumChunksPerIsacBlock = 3;
void GenerateNoise(std::vector<int16_t>* data) {
for (size_t i = 0; i < data->size(); ++i) {
// std::rand returns between 0 and RAND_MAX, but this will work because it
// wraps into some random place.
(*data)[i] = std::rand();
}
}
} // namespace
TEST(VoiceActivityDetectorTest, ConstructorSetsDefaultValues) {
const float kDefaultVoiceValue = 1.f;
VoiceActivityDetector vad;
std::vector<double> p = vad.chunkwise_voice_probabilities();
std::vector<double> rms = vad.chunkwise_rms();
EXPECT_EQ(p.size(), 0u);
EXPECT_EQ(rms.size(), 0u);
EXPECT_FLOAT_EQ(vad.last_voice_probability(), kDefaultVoiceValue);
}
TEST(VoiceActivityDetectorTest, Speech16kHzHasHighVoiceProbabilities) {
const int kSampleRateHz = 16000;
const int kLength10Ms = kSampleRateHz / 100;
VoiceActivityDetector vad;
std::vector<int16_t> data(kLength10Ms);
float mean_probability = 0.f;
FILE* pcm_file =
fopen(test::ResourcePath("audio_processing/transient/audio16kHz", "pcm")
.c_str(),
"rb");
ASSERT_TRUE(pcm_file != nullptr);
// The silences in the file are skipped to get a more robust voice probability
// for speech.
ASSERT_EQ(fseek(pcm_file, kStartTimeSec * kSampleRateHz * sizeof(data[0]),
SEEK_SET),
0);
size_t num_chunks = 0;
while (fread(&data[0], sizeof(data[0]), data.size(), pcm_file) ==
data.size()) {
vad.ProcessChunk(&data[0], data.size(), kSampleRateHz);
mean_probability += vad.last_voice_probability();
++num_chunks;
}
mean_probability /= num_chunks;
EXPECT_GT(mean_probability, kMeanSpeechProbability);
}
TEST(VoiceActivityDetectorTest, Speech32kHzHasHighVoiceProbabilities) {
const int kSampleRateHz = 32000;
const int kLength10Ms = kSampleRateHz / 100;
VoiceActivityDetector vad;
std::vector<int16_t> data(kLength10Ms);
float mean_probability = 0.f;
FILE* pcm_file =
fopen(test::ResourcePath("audio_processing/transient/audio32kHz", "pcm")
.c_str(),
"rb");
ASSERT_TRUE(pcm_file != nullptr);
// The silences in the file are skipped to get a more robust voice probability
// for speech.
ASSERT_EQ(fseek(pcm_file, kStartTimeSec * kSampleRateHz * sizeof(data[0]),
SEEK_SET),
0);
size_t num_chunks = 0;
while (fread(&data[0], sizeof(data[0]), data.size(), pcm_file) ==
data.size()) {
vad.ProcessChunk(&data[0], data.size(), kSampleRateHz);
mean_probability += vad.last_voice_probability();
++num_chunks;
}
mean_probability /= num_chunks;
EXPECT_GT(mean_probability, kMeanSpeechProbability);
}
TEST(VoiceActivityDetectorTest, Noise16kHzHasLowVoiceProbabilities) {
VoiceActivityDetector vad;
std::vector<int16_t> data(kLength10Ms);
float max_probability = 0.f;
std::srand(42);
for (size_t i = 0; i < kNumChunks; ++i) {
GenerateNoise(&data);
vad.ProcessChunk(&data[0], data.size(), kSampleRateHz);
// Before the |vad has enough data to process an ISAC block it will return
// the default value, 1.f, which would ruin the |max_probability| value.
if (i > kNumChunksPerIsacBlock) {
max_probability = std::max(max_probability, vad.last_voice_probability());
}
}
EXPECT_LT(max_probability, kMaxNoiseProbability);
}
TEST(VoiceActivityDetectorTest, Noise32kHzHasLowVoiceProbabilities) {
VoiceActivityDetector vad;
std::vector<int16_t> data(2 * kLength10Ms);
float max_probability = 0.f;
std::srand(42);
for (size_t i = 0; i < kNumChunks; ++i) {
GenerateNoise(&data);
vad.ProcessChunk(&data[0], data.size(), 2 * kSampleRateHz);
// Before the |vad has enough data to process an ISAC block it will return
// the default value, 1.f, which would ruin the |max_probability| value.
if (i > kNumChunksPerIsacBlock) {
max_probability = std::max(max_probability, vad.last_voice_probability());
}
}
EXPECT_LT(max_probability, kMaxNoiseProbability);
}
} // namespace webrtc