Fine tune the IntelligibilityEnhancer
Label less chunks as speech, adapt slower and be more conservative with the maximum gain it can apply. Review-Url: https://codereview.webrtc.org/2087623003 Cr-Commit-Position: refs/heads/master@{#13242}
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@ -31,11 +31,11 @@ const float kClipFreqKhz = 0.2f;
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const float kKbdAlpha = 1.5f;
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const float kLambdaBot = -1.f; // Extreme values in bisection
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const float kLambdaTop = -1e-5f; // search for lamda.
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const float kVoiceProbabilityThreshold = 0.02f;
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const float kVoiceProbabilityThreshold = 0.5f;
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// Number of chunks after voice activity which is still considered speech.
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const size_t kSpeechOffsetDelay = 80;
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const float kDecayRate = 0.994f; // Power estimation decay rate.
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const float kMaxRelativeGainChange = 0.006f;
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const size_t kSpeechOffsetDelay = 10;
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const float kDecayRate = 0.995f; // Power estimation decay rate.
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const float kMaxRelativeGainChange = 0.005f;
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const float kRho = 0.0004f; // Default production and interpretation SNR.
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const float kPowerNormalizationFactor = 1.f / (1 << 30);
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const float kMaxActiveSNR = 128.f; // 21dB
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@ -409,7 +409,7 @@ TEST_F(IntelligibilityEnhancerTest, TestSolveForGains) {
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TEST_F(IntelligibilityEnhancerTest, TestNoiseGainHasExpectedResult) {
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const int kGainDB = 6;
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const float kGainFactor = std::pow(10.f, kGainDB / 20.f);
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const float kTolerance = 0.003f;
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const float kTolerance = 0.007f;
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std::vector<float> noise(kNumNoiseBins);
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std::vector<float> noise_psd(kNumNoiseBins);
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std::generate(noise.begin(), noise.end(), float_rand);
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@ -23,7 +23,7 @@ namespace intelligibility {
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namespace {
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const float kMinFactor = 0.01f;
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const float kMaxFactor = 1000.f;
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const float kMaxFactor = 100.f;
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// Return |current| changed towards |target|, with the relative change being at
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// most |limit|.
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