| Index: webrtc/modules/audio_processing/intelligibility/intelligibility_enhancer.cc
|
| diff --git a/webrtc/modules/audio_processing/intelligibility/intelligibility_enhancer.cc b/webrtc/modules/audio_processing/intelligibility/intelligibility_enhancer.cc
|
| index 04d36545216879d464065a62d773f3abb8d74dbd..0ec73dafd7c9b7861825bb2efc458f2cec189755 100644
|
| --- a/webrtc/modules/audio_processing/intelligibility/intelligibility_enhancer.cc
|
| +++ b/webrtc/modules/audio_processing/intelligibility/intelligibility_enhancer.cc
|
| @@ -29,8 +29,8 @@ const int kWindowSizeMs = 16;
|
| const int kChunkSizeMs = 10; // Size provided by APM.
|
| const float kClipFreqKhz = 0.2f;
|
| const float kKbdAlpha = 1.5f;
|
| -const float kLambdaBot = -1.0f; // Extreme values in bisection
|
| -const float kLambdaTop = -1e-5f; // search for lamda.
|
| +const double kLambdaBot = -1.0 / (1 << 30); // Extreme values in bisection
|
| +const double kLambdaTop = -1e-5 / (1 << 30); // search for lamda.
|
| const float kVoiceProbabilityThreshold = 0.02f;
|
| // Number of chunks after voice activity which is still considered speech.
|
| const size_t kSpeechOffsetDelay = 80;
|
| @@ -162,12 +162,12 @@ void IntelligibilityEnhancer::SolveForLambda(float power_target) {
|
|
|
| const float reciprocal_power_target =
|
| 1.f / (power_target + std::numeric_limits<float>::epsilon());
|
| - float lambda_bot = kLambdaBot;
|
| - float lambda_top = kLambdaTop;
|
| + double lambda_bot = kLambdaBot;
|
| + double lambda_top = kLambdaTop;
|
| float power_ratio = 2.f; // Ratio of achieved power to target power.
|
| int iters = 0;
|
| while (std::fabs(power_ratio - 1.f) > kConvergeThresh && iters <= kMaxIters) {
|
| - const float lambda = (lambda_bot + lambda_top) / 2.f;
|
| + const double lambda = (lambda_bot + lambda_top) / 2.0;
|
| SolveForGainsGivenLambda(lambda, start_freq_, gains_eq_.data());
|
| const float power =
|
| DotProduct(gains_eq_.data(), filtered_clear_pow_.data(), bank_size_);
|
| @@ -267,7 +267,7 @@ std::vector<std::vector<float>> IntelligibilityEnhancer::CreateErbBank(
|
| return filter_bank;
|
| }
|
|
|
| -void IntelligibilityEnhancer::SolveForGainsGivenLambda(float lambda,
|
| +void IntelligibilityEnhancer::SolveForGainsGivenLambda(double lambda,
|
| size_t start_freq,
|
| float* sols) {
|
| const float kMinPower = 1e-5f;
|
| @@ -284,19 +284,19 @@ void IntelligibilityEnhancer::SolveForGainsGivenLambda(float lambda,
|
| if (pow_x0[n] < kMinPower || pow_n0[n] < kMinPower) {
|
| sols[n] = 1.f;
|
| } else {
|
| - const float gamma0 = 0.5f * kRho * pow_x0[n] * pow_n0[n] +
|
| + const double gamma0 = 0.5 * kRho * pow_x0[n] * pow_n0[n] +
|
| lambda * pow_x0[n] * pow_n0[n] * pow_n0[n];
|
| - const float beta0 =
|
| - lambda * pow_x0[n] * (2.f - kRho) * pow_x0[n] * pow_n0[n];
|
| - const float alpha0 =
|
| - lambda * pow_x0[n] * (1.f - kRho) * pow_x0[n] * pow_x0[n];
|
| - RTC_DCHECK_LT(alpha0, 0.f);
|
| + const double beta0 =
|
| + lambda * pow_x0[n] * (2.0 - kRho) * pow_x0[n] * pow_n0[n];
|
| + const double alpha0 =
|
| + lambda * pow_x0[n] * (1.0 - kRho) * pow_x0[n] * pow_x0[n];
|
| + RTC_DCHECK_LT(alpha0, 0.0);
|
| // The quadratic equation should always have real roots, but to guard
|
| // against numerical errors we limit it to a minimum of zero.
|
| sols[n] = std::max(
|
| - 0.f, (-beta0 - std::sqrt(std::max(
|
| - 0.f, beta0 * beta0 - 4.f * alpha0 * gamma0))) /
|
| - (2.f * alpha0));
|
| + 0.0, (-beta0 - std::sqrt(std::max(
|
| + 0.0, beta0 * beta0 - 4.0 * alpha0 * gamma0))) /
|
| + (2.0 * alpha0));
|
| }
|
| }
|
| }
|
|
|