Moved the filter calculation from analyze to process in ns_core
It makes sense to have it there if the analyze and process methods are called in different stages. Tested over the entire QA set for bit exactness. BUG=webrtc:3811 R=bjornv@webrtc.org Review URL: https://webrtc-codereview.appspot.com/29549004 git-svn-id: http://webrtc.googlecode.com/svn/trunk@7287 4adac7df-926f-26a2-2b94-8c16560cd09d
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aluebs@webrtc.org
parent
634c926928
commit
275dac2c1d
@ -764,22 +764,18 @@ int WebRtcNs_AnalyzeCore(NSinst_t* inst, float* speechFrame) {
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int updateParsFlag;
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float energy;
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float signalEnergy, sumMagn;
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float snrPrior, currentEstimateStsa;
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float tmpFloat1, tmpFloat2, tmpFloat3, probSpeech, probNonSpeech;
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float gammaNoiseTmp, gammaNoiseOld;
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float noiseUpdateTmp, fTmp;
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float winData[ANAL_BLOCKL_MAX];
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float magn[HALF_ANAL_BLOCKL], noise[HALF_ANAL_BLOCKL];
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float theFilter[HALF_ANAL_BLOCKL], theFilterTmp[HALF_ANAL_BLOCKL];
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float snrLocPost[HALF_ANAL_BLOCKL], snrLocPrior[HALF_ANAL_BLOCKL];
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float previousEstimateStsa[HALF_ANAL_BLOCKL];
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float real[ANAL_BLOCKL_MAX], imag[HALF_ANAL_BLOCKL];
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// Variables during startup
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float sum_log_i = 0.0;
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float sum_log_i_square = 0.0;
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float sum_log_magn = 0.0;
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float sum_log_i_log_magn = 0.0;
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float parametric_noise = 0.0;
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float parametric_exp = 0.0;
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float parametric_num = 0.0;
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@ -834,8 +830,6 @@ int WebRtcNs_AnalyzeCore(NSinst_t* inst, float* speechFrame) {
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(float)(real[inst->magnLen - 1] * real[inst->magnLen - 1]);
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sumMagn = magn[0] + magn[inst->magnLen - 1];
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if (inst->blockInd < END_STARTUP_SHORT) {
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inst->initMagnEst[0] += magn[0];
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inst->initMagnEst[inst->magnLen - 1] += magn[inst->magnLen - 1];
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tmpFloat2 = log((float)(inst->magnLen - 1));
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sum_log_i = tmpFloat2;
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sum_log_i_square = tmpFloat2 * tmpFloat2;
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@ -853,7 +847,6 @@ int WebRtcNs_AnalyzeCore(NSinst_t* inst, float* speechFrame) {
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magn[i] = ((float)sqrt(fTmp)) + 1.0f;
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sumMagn += magn[i];
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if (inst->blockInd < END_STARTUP_SHORT) {
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inst->initMagnEst[i] += magn[i];
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if (i >= kStartBand) {
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tmpFloat2 = log((float)i);
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sum_log_i += tmpFloat2;
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@ -901,31 +894,29 @@ int WebRtcNs_AnalyzeCore(NSinst_t* inst, float* speechFrame) {
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inst->pinkNoiseExp += tmpFloat3;
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// Calculate frequency independent parts of parametric noise estimate.
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if (inst->pinkNoiseExp == 0.0f) {
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// Use white noise estimate
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parametric_noise = inst->whiteNoiseLevel;
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} else {
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if (inst->pinkNoiseExp > 0.0f) {
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// Use pink noise estimate
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parametric_num =
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exp(inst->pinkNoiseNumerator / (float)(inst->blockInd + 1));
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parametric_num *= (float)(inst->blockInd + 1);
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parametric_exp = inst->pinkNoiseExp / (float)(inst->blockInd + 1);
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parametric_noise =
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parametric_num / pow((float)kStartBand, parametric_exp);
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}
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for (i = 0; i < inst->magnLen; i++) {
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// Estimate the background noise using the white and pink noise
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// parameters
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if ((inst->pinkNoiseExp > 0.0f) && (i >= kStartBand)) {
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if (inst->pinkNoiseExp == 0.0f) {
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// Use white noise estimate
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inst->parametricNoise[i] = inst->whiteNoiseLevel;
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} else {
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// Use pink noise estimate
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parametric_noise = parametric_num / pow((float)i, parametric_exp);
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float use_band = (float)(i < kStartBand ? kStartBand : i);
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inst->parametricNoise[i] =
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parametric_num / pow(use_band, parametric_exp);
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}
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theFilterTmp[i] =
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(inst->initMagnEst[i] - inst->overdrive * parametric_noise);
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theFilterTmp[i] /= (inst->initMagnEst[i] + (float)0.0001);
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// Weight quantile noise with modeled noise
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noise[i] *= (inst->blockInd);
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tmpFloat2 = parametric_noise * (END_STARTUP_SHORT - inst->blockInd);
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tmpFloat2 =
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inst->parametricNoise[i] * (END_STARTUP_SHORT - inst->blockInd);
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noise[i] += (tmpFloat2 / (float)(inst->blockInd + 1));
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noise[i] /= END_STARTUP_SHORT;
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}
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@ -949,12 +940,12 @@ int WebRtcNs_AnalyzeCore(NSinst_t* inst, float* speechFrame) {
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}
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// previous post snr
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// previous estimate: based on previous frame with gain filter
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previousEstimateStsa[i] = inst->magnPrev[i] /
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inst->previousEstimateStsa[i] = inst->magnPrev[i] /
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(inst->noisePrev[i] + (float)0.0001) *
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(inst->smooth[i]);
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// DD estimate is sum of two terms: current estimate and previous estimate
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// directed decision update of snrPrior
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snrLocPrior[i] = DD_PR_SNR * previousEstimateStsa[i] +
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snrLocPrior[i] = DD_PR_SNR * inst->previousEstimateStsa[i] +
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((float)1.0 - DD_PR_SNR) * snrLocPost[i];
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// post and prior snr needed for step 2
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} // end of loop over freqs
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@ -1037,57 +1028,9 @@ int WebRtcNs_AnalyzeCore(NSinst_t* inst, float* speechFrame) {
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} // end of freq loop
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// done with step 2: noise update
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// STEP 3: compute dd update of prior snr and post snr based on new noise
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// estimate
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for (i = 0; i < inst->magnLen; i++) {
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// post and prior snr
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currentEstimateStsa = (float)0.0;
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if (magn[i] > noise[i]) {
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currentEstimateStsa = magn[i] / (noise[i] + (float)0.0001) - (float)1.0;
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}
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// DD estimate is sume of two terms: current estimate and previous
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// estimate
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// directed decision update of snrPrior
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snrPrior = DD_PR_SNR * previousEstimateStsa[i] +
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((float)1.0 - DD_PR_SNR) * currentEstimateStsa;
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// gain filter
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tmpFloat1 = inst->overdrive + snrPrior;
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tmpFloat2 = (float)snrPrior / tmpFloat1;
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theFilter[i] = (float)tmpFloat2;
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} // end of loop over freqs
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// done with step3
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for (i = 0; i < inst->magnLen; i++) {
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// flooring bottom
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if (theFilter[i] < inst->denoiseBound) {
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theFilter[i] = inst->denoiseBound;
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}
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// flooring top
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if (theFilter[i] > (float)1.0) {
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theFilter[i] = 1.0;
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}
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if (inst->blockInd < END_STARTUP_SHORT) {
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// flooring bottom
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if (theFilterTmp[i] < inst->denoiseBound) {
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theFilterTmp[i] = inst->denoiseBound;
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}
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// flooring top
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if (theFilterTmp[i] > (float)1.0) {
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theFilterTmp[i] = 1.0;
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}
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// Weight the two suppression filters
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theFilter[i] *= (inst->blockInd);
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theFilterTmp[i] *= (END_STARTUP_SHORT - inst->blockInd);
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theFilter[i] += theFilterTmp[i];
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theFilter[i] /= (END_STARTUP_SHORT);
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}
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// smoothing
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inst->smooth[i] = theFilter[i];
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}
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// keep track of noise and magn spectrum for next frame
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// keep track of noise spectrum for next frame
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for (i = 0; i < inst->magnLen; i++) {
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inst->noisePrev[i] = noise[i];
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inst->magnPrev[i] = magn[i];
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}
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} // end of if inst->outLen == 0
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@ -1104,8 +1047,13 @@ int WebRtcNs_ProcessCore(NSinst_t* inst,
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int i;
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float energy1, energy2, gain, factor, factor1, factor2;
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float snrPrior, currentEstimateStsa;
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float tmpFloat1, tmpFloat2;
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float fTmp;
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float fout[BLOCKL_MAX];
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float winData[ANAL_BLOCKL_MAX];
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float magn[HALF_ANAL_BLOCKL];
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float theFilter[HALF_ANAL_BLOCKL], theFilterTmp[HALF_ANAL_BLOCKL];
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float real[ANAL_BLOCKL_MAX], imag[HALF_ANAL_BLOCKL];
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// SWB variables
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@ -1196,17 +1144,81 @@ int WebRtcNs_ProcessCore(NSinst_t* inst,
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imag[0] = 0;
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real[0] = winData[0];
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magn[0] = (float)(fabs(real[0]) + 1.0f);
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imag[inst->magnLen - 1] = 0;
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real[inst->magnLen - 1] = winData[1];
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magn[inst->magnLen - 1] = (float)(fabs(real[inst->magnLen - 1]) + 1.0f);
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if (inst->blockInd < END_STARTUP_SHORT) {
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inst->initMagnEst[0] += magn[0];
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inst->initMagnEst[inst->magnLen - 1] += magn[inst->magnLen - 1];
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}
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for (i = 1; i < inst->magnLen - 1; i++) {
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real[i] = winData[2 * i];
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imag[i] = winData[2 * i + 1];
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// magnitude spectrum
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fTmp = real[i] * real[i];
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fTmp += imag[i] * imag[i];
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magn[i] = ((float)sqrt(fTmp)) + 1.0f;
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if (inst->blockInd < END_STARTUP_SHORT) {
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inst->initMagnEst[i] += magn[i];
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}
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}
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// Compute dd update of prior snr and post snr based on new noise estimate
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for (i = 0; i < inst->magnLen; i++) {
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// post and prior snr
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currentEstimateStsa = (float)0.0;
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if (magn[i] > inst->noisePrev[i]) {
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currentEstimateStsa =
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magn[i] / (inst->noisePrev[i] + (float)0.0001) - (float)1.0;
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}
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// DD estimate is sume of two terms: current estimate and previous
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// estimate
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// directed decision update of snrPrior
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snrPrior = DD_PR_SNR * inst->previousEstimateStsa[i] +
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((float)1.0 - DD_PR_SNR) * currentEstimateStsa;
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// gain filter
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tmpFloat1 = inst->overdrive + snrPrior;
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tmpFloat2 = (float)snrPrior / tmpFloat1;
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theFilter[i] = (float)tmpFloat2;
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} // end of loop over freqs
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for (i = 0; i < inst->magnLen; i++) {
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// flooring bottom
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if (theFilter[i] < inst->denoiseBound) {
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theFilter[i] = inst->denoiseBound;
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}
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// flooring top
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if (theFilter[i] > (float)1.0) {
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theFilter[i] = 1.0;
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}
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if (inst->blockInd < END_STARTUP_SHORT) {
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theFilterTmp[i] =
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(inst->initMagnEst[i] - inst->overdrive * inst->parametricNoise[i]);
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theFilterTmp[i] /= (inst->initMagnEst[i] + (float)0.0001);
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// flooring bottom
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if (theFilterTmp[i] < inst->denoiseBound) {
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theFilterTmp[i] = inst->denoiseBound;
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}
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// flooring top
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if (theFilterTmp[i] > (float)1.0) {
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theFilterTmp[i] = 1.0;
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}
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// Weight the two suppression filters
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theFilter[i] *= (inst->blockInd);
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theFilterTmp[i] *= (END_STARTUP_SHORT - inst->blockInd);
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theFilter[i] += theFilterTmp[i];
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theFilter[i] /= (END_STARTUP_SHORT);
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}
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// smoothing
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inst->smooth[i] = theFilter[i];
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real[i] *= inst->smooth[i];
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imag[i] *= inst->smooth[i];
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}
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// keep track of magn spectrum for next frame
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for (i = 0; i < inst->magnLen; i++) {
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inst->magnPrev[i] = magn[i];
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}
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// back to time domain
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winData[0] = real[0];
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winData[1] = real[inst->magnLen - 1];
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@ -72,6 +72,7 @@ typedef struct NSinst_t_ {
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int counter[SIMULT];
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int updates;
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// parameters for Wiener filter
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float previousEstimateStsa[HALF_ANAL_BLOCKL];
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float smooth[HALF_ANAL_BLOCKL];
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float overdrive;
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float denoiseBound;
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@ -97,6 +98,7 @@ typedef struct NSinst_t_ {
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float initMagnEst[HALF_ANAL_BLOCKL]; // initial magnitude spectrum estimate
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float pinkNoiseNumerator; // pink noise parameter: numerator
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float pinkNoiseExp; // pink noise parameter: power of freq
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float parametricNoise[HALF_ANAL_BLOCKL];
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NSParaExtract_t featureExtractionParams; // parameters for feature extraction
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// histograms for parameter estimation
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int histLrt[HIST_PAR_EST];
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