zqz/platform-external-webrtc
1
0
Fork 0
Code Issues Pull Requests Actions Packages Projects Releases Wiki Activity

Break out ComputeSnr function in ns_core

Browse Source 
This is done in order to make the code more readible and maintainable.
The output is bit-exact.

BUG=webrtc:3811
R=bjornv@webrtc.org, kwiberg@webrtc.org

Review URL: https://webrtc-codereview.appspot.com/31729004

git-svn-id: http://webrtc.googlecode.com/svn/trunk@7511 4adac7df-926f-26a2-2b94-8c16560cd09d
This commit is contained in:
aluebs@webrtc.org
2014-10-23 19:34:14 +00:00
parent 0d3e254c89
commit 8454ad88ed
1 changed files with 34 additions and 21 deletions
Download Patch File Download Diff File Expand all files Collapse all files

55
webrtc/modules/audio_processing/ns/ns_core.c
View File

@ -588,6 +588,38 @@ void WebRtcNs_ComputeSpectralFlatness(NSinst_t* inst, float* magnIn) {
// done with flatness feature
}
// Compute prior and post snr based on quantile noise estimation.
// Compute DD estimate of prior SNR.
// Inputs:
// * |magn| is the signal magnitude spectrum estimate.
// * |noise| is the magnitude noise spectrum estimate.
// Outputs:
// * |snrLocPrior| is the computed prior SNR.
// * |snrLocPost| is the computed post SNR.
static void ComputeSnr(const NSinst_t* const self,
const float* magn,
const float* noise,
float* snrLocPrior,
float* snrLocPost) {
int i;
for (i = 0; i < self->magnLen; i++) {
// Previous post SNR.
// Previous estimate: based on previous frame with gain filter.
float previousEstimateStsa = self->magnPrevAnalyze[i] /
(self->noisePrev[i] + 0.0001f) * self->smooth[i];
// Post SNR.
snrLocPost[i] = 0.f;
if (magn[i] > noise[i]) {
snrLocPost[i] = magn[i] / (noise[i] + 0.0001f) - 1.f;
}
// DD estimate is sum of two terms: current estimate and previous estimate
// directed decision update of snrPrior.
snrLocPrior[i] =
DD_PR_SNR * previousEstimateStsa + (1.f - DD_PR_SNR) * snrLocPost[i];
} // End of loop over frequencies.
}
// Compute the difference measure between input spectrum and a template/learned
// noise spectrum
// magnIn is the input spectrum
@ -857,7 +889,6 @@ int WebRtcNs_AnalyzeCore(NSinst_t* inst, float* speechFrame) {
float winData[ANAL_BLOCKL_MAX];
float magn[HALF_ANAL_BLOCKL], noise[HALF_ANAL_BLOCKL];
float snrLocPost[HALF_ANAL_BLOCKL], snrLocPrior[HALF_ANAL_BLOCKL];
float previousEstimateStsa[HALF_ANAL_BLOCKL];
float real[ANAL_BLOCKL_MAX], imag[HALF_ANAL_BLOCKL];
// Variables during startup
float sum_log_i = 0.0;
@ -1006,26 +1037,8 @@ int WebRtcNs_AnalyzeCore(NSinst_t* inst, float* speechFrame) {
inst->featureData[5] /= (inst->blockInd + 1);
}
// start processing at frames == converged+1
// STEP 1: compute prior and post snr based on quantile noise est
// compute DD estimate of prior SNR: needed for new method
for (i = 0; i < inst->magnLen; i++) {
// post snr
snrLocPost[i] = 0.f;
if (magn[i] > noise[i]) {
snrLocPost[i] = magn[i] / (noise[i] + 0.0001f) - 1.f;
}
// previous post snr
// previous estimate: based on previous frame with gain filter
previousEstimateStsa[i] = inst->magnPrevAnalyze[i] /
(inst->noisePrev[i] + 0.0001f) * inst->smooth[i];
// DD estimate is sum of two terms: current estimate and previous estimate
// directed decision update of snrPrior
snrLocPrior[i] =
DD_PR_SNR * previousEstimateStsa[i] + (1.f - DD_PR_SNR) * snrLocPost[i];
// post and prior snr needed for step 2
} // end of loop over freqs
// done with step 1: dd computation of prior and post snr
// Post and prior SNR needed for WebRtcNs_SpeechNoiseProb.
ComputeSnr(inst, magn, noise, snrLocPrior, snrLocPost);
// STEP 2: compute speech/noise likelihood
// compute difference of input spectrum with learned/estimated noise