1 /* 2 * Copyright (c) 2015 The WebRTC project authors. All Rights Reserved. 3 * 4 * Use of this source code is governed by a BSD-style license 5 * that can be found in the LICENSE file in the root of the source 6 * tree. An additional intellectual property rights grant can be found 7 * in the file PATENTS. All contributing project authors may 8 * be found in the AUTHORS file in the root of the source tree. 9 */ 10 11 // 12 // Unit tests for intelligibility enhancer. 13 // 14 15 #include <math.h> 16 #include <stdlib.h> 17 #include <algorithm> 18 #include <vector> 19 20 #include "testing/gtest/include/gtest/gtest.h" 21 #include "webrtc/base/arraysize.h" 22 #include "webrtc/base/scoped_ptr.h" 23 #include "webrtc/common_audio/signal_processing/include/signal_processing_library.h" 24 #include "webrtc/modules/audio_processing/intelligibility/intelligibility_enhancer.h" 25 26 namespace webrtc { 27 28 namespace { 29 30 // Target output for ERB create test. Generated with matlab. 31 const float kTestCenterFreqs[] = { 32 13.169f, 26.965f, 41.423f, 56.577f, 72.461f, 89.113f, 106.57f, 124.88f, 33 144.08f, 164.21f, 185.34f, 207.5f, 230.75f, 255.16f, 280.77f, 307.66f, 34 335.9f, 365.56f, 396.71f, 429.44f, 463.84f, 500.f}; 35 const float kTestFilterBank[][2] = {{0.055556f, 0.f}, 36 {0.055556f, 0.f}, 37 {0.055556f, 0.f}, 38 {0.055556f, 0.f}, 39 {0.055556f, 0.f}, 40 {0.055556f, 0.f}, 41 {0.055556f, 0.f}, 42 {0.055556f, 0.f}, 43 {0.055556f, 0.f}, 44 {0.055556f, 0.f}, 45 {0.055556f, 0.f}, 46 {0.055556f, 0.f}, 47 {0.055556f, 0.f}, 48 {0.055556f, 0.f}, 49 {0.055556f, 0.f}, 50 {0.055556f, 0.f}, 51 {0.055556f, 0.f}, 52 {0.055556f, 0.2f}, 53 {0, 0.2f}, 54 {0, 0.2f}, 55 {0, 0.2f}, 56 {0, 0.2f}}; 57 static_assert(arraysize(kTestCenterFreqs) == arraysize(kTestFilterBank), 58 "Test filterbank badly initialized."); 59 60 // Target output for gain solving test. Generated with matlab. 61 const size_t kTestStartFreq = 12; // Lowest integral frequency for ERBs. 62 const float kTestZeroVar[] = {1.f, 1.f, 1.f, 1.f, 1.f, 1.f, 1.f, 1.f, 63 1.f, 1.f, 1.f, 0.f, 0.f, 0.f, 0.f, 0.f, 64 0.f, 0.f, 0.f, 0.f, 0.f, 0.f}; 65 static_assert(arraysize(kTestCenterFreqs) == arraysize(kTestZeroVar), 66 "Variance test data badly initialized."); 67 const float kTestNonZeroVarLambdaTop[] = { 68 1.f, 1.f, 1.f, 1.f, 1.f, 1.f, 1.f, 1.f, 69 1.f, 1.f, 1.f, 0.f, 0.f, 0.0351f, 0.0636f, 0.0863f, 70 0.1037f, 0.1162f, 0.1236f, 0.1251f, 0.1189f, 0.0993f}; 71 static_assert(arraysize(kTestCenterFreqs) == 72 arraysize(kTestNonZeroVarLambdaTop), 73 "Variance test data badly initialized."); 74 const float kMaxTestError = 0.005f; 75 76 // Enhancer initialization parameters. 77 const int kSamples = 2000; 78 const int kSampleRate = 1000; 79 const int kNumChannels = 1; 80 const int kFragmentSize = kSampleRate / 100; 81 82 } // namespace 83 84 using std::vector; 85 using intelligibility::VarianceArray; 86 87 class IntelligibilityEnhancerTest : public ::testing::Test { 88 protected: 89 IntelligibilityEnhancerTest() 90 : clear_data_(kSamples), noise_data_(kSamples), orig_data_(kSamples) { 91 config_.sample_rate_hz = kSampleRate; 92 enh_.reset(new IntelligibilityEnhancer(config_)); 93 } 94 95 bool CheckUpdate(VarianceArray::StepType step_type) { 96 config_.sample_rate_hz = kSampleRate; 97 config_.var_type = step_type; 98 enh_.reset(new IntelligibilityEnhancer(config_)); 99 float* clear_cursor = &clear_data_[0]; 100 float* noise_cursor = &noise_data_[0]; 101 for (int i = 0; i < kSamples; i += kFragmentSize) { 102 enh_->AnalyzeCaptureAudio(&noise_cursor, kSampleRate, kNumChannels); 103 enh_->ProcessRenderAudio(&clear_cursor, kSampleRate, kNumChannels); 104 clear_cursor += kFragmentSize; 105 noise_cursor += kFragmentSize; 106 } 107 for (int i = 0; i < kSamples; i++) { 108 if (std::fabs(clear_data_[i] - orig_data_[i]) > kMaxTestError) { 109 return true; 110 } 111 } 112 return false; 113 } 114 115 IntelligibilityEnhancer::Config config_; 116 rtc::scoped_ptr<IntelligibilityEnhancer> enh_; 117 vector<float> clear_data_; 118 vector<float> noise_data_; 119 vector<float> orig_data_; 120 }; 121 122 // For each class of generated data, tests that render stream is 123 // updated when it should be for each variance update method. 124 TEST_F(IntelligibilityEnhancerTest, TestRenderUpdate) { 125 vector<VarianceArray::StepType> step_types; 126 step_types.push_back(VarianceArray::kStepInfinite); 127 step_types.push_back(VarianceArray::kStepDecaying); 128 step_types.push_back(VarianceArray::kStepWindowed); 129 step_types.push_back(VarianceArray::kStepBlocked); 130 step_types.push_back(VarianceArray::kStepBlockBasedMovingAverage); 131 std::fill(noise_data_.begin(), noise_data_.end(), 0.0f); 132 std::fill(orig_data_.begin(), orig_data_.end(), 0.0f); 133 for (auto step_type : step_types) { 134 std::fill(clear_data_.begin(), clear_data_.end(), 0.0f); 135 EXPECT_FALSE(CheckUpdate(step_type)); 136 } 137 std::srand(1); 138 auto float_rand = []() { return std::rand() * 2.f / RAND_MAX - 1; }; 139 std::generate(noise_data_.begin(), noise_data_.end(), float_rand); 140 for (auto step_type : step_types) { 141 EXPECT_FALSE(CheckUpdate(step_type)); 142 } 143 for (auto step_type : step_types) { 144 std::generate(clear_data_.begin(), clear_data_.end(), float_rand); 145 orig_data_ = clear_data_; 146 EXPECT_TRUE(CheckUpdate(step_type)); 147 } 148 } 149 150 // Tests ERB bank creation, comparing against matlab output. 151 TEST_F(IntelligibilityEnhancerTest, TestErbCreation) { 152 ASSERT_EQ(arraysize(kTestCenterFreqs), enh_->bank_size_); 153 for (size_t i = 0; i < enh_->bank_size_; ++i) { 154 EXPECT_NEAR(kTestCenterFreqs[i], enh_->center_freqs_[i], kMaxTestError); 155 ASSERT_EQ(arraysize(kTestFilterBank[0]), enh_->freqs_); 156 for (size_t j = 0; j < enh_->freqs_; ++j) { 157 EXPECT_NEAR(kTestFilterBank[i][j], enh_->filter_bank_[i][j], 158 kMaxTestError); 159 } 160 } 161 } 162 163 // Tests analytic solution for optimal gains, comparing 164 // against matlab output. 165 TEST_F(IntelligibilityEnhancerTest, TestSolveForGains) { 166 ASSERT_EQ(kTestStartFreq, enh_->start_freq_); 167 vector<float> sols(enh_->bank_size_); 168 float lambda = -0.001f; 169 for (size_t i = 0; i < enh_->bank_size_; i++) { 170 enh_->filtered_clear_var_[i] = 0.0f; 171 enh_->filtered_noise_var_[i] = 0.0f; 172 enh_->rho_[i] = 0.02f; 173 } 174 enh_->SolveForGainsGivenLambda(lambda, enh_->start_freq_, &sols[0]); 175 for (size_t i = 0; i < enh_->bank_size_; i++) { 176 EXPECT_NEAR(kTestZeroVar[i], sols[i], kMaxTestError); 177 } 178 for (size_t i = 0; i < enh_->bank_size_; i++) { 179 enh_->filtered_clear_var_[i] = static_cast<float>(i + 1); 180 enh_->filtered_noise_var_[i] = static_cast<float>(enh_->bank_size_ - i); 181 } 182 enh_->SolveForGainsGivenLambda(lambda, enh_->start_freq_, &sols[0]); 183 for (size_t i = 0; i < enh_->bank_size_; i++) { 184 EXPECT_NEAR(kTestNonZeroVarLambdaTop[i], sols[i], kMaxTestError); 185 } 186 lambda = -1.0; 187 enh_->SolveForGainsGivenLambda(lambda, enh_->start_freq_, &sols[0]); 188 for (size_t i = 0; i < enh_->bank_size_; i++) { 189 EXPECT_NEAR(kTestZeroVar[i], sols[i], kMaxTestError); 190 } 191 } 192 193 } // namespace webrtc 194
