• Home
  • Line#
  • Scopes#
  • Navigate#
  • Raw
  • Download
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:
IntelligibilityEnhancerTest()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 
CheckUpdate(VarianceArray::StepType step_type)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.
TEST_F(IntelligibilityEnhancerTest,TestRenderUpdate)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.
TEST_F(IntelligibilityEnhancerTest,TestErbCreation)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.
TEST_F(IntelligibilityEnhancerTest,TestSolveForGains)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