// // Copyright © 2020 Arm Ltd and Contributors. All rights reserved. // SPDX-License-Identifier: MIT // #include #include #include "MFCC.hpp" #include "MathUtils.hpp" MfccParams::MfccParams( const float samplingFreq, const int numFbankBins, const float melLoFreq, const float melHiFreq, const int numMfccFeats, const int frameLen, const bool useHtkMethod, const int numMfccVectors): m_samplingFreq(samplingFreq), m_numFbankBins(numFbankBins), m_melLoFreq(melLoFreq), m_melHiFreq(melHiFreq), m_numMfccFeatures(numMfccFeats), m_frameLen(frameLen), m_numMfccVectors(numMfccVectors), /* Smallest power of 2 >= frame length. */ m_frameLenPadded(pow(2, ceil((log(frameLen)/log(2))))), m_useHtkMethod(useHtkMethod) {} std::string MfccParams::Str() { char strC[1024]; snprintf(strC, sizeof(strC) - 1, "\n \ \n\t Sampling frequency: %f\ \n\t Number of filter banks: %u\ \n\t Mel frequency limit (low): %f\ \n\t Mel frequency limit (high): %f\ \n\t Number of MFCC features: %u\ \n\t Frame length: %u\ \n\t Padded frame length: %u\ \n\t Using HTK for Mel scale: %s\n", this->m_samplingFreq, this->m_numFbankBins, this->m_melLoFreq, this->m_melHiFreq, this->m_numMfccFeatures, this->m_frameLen, this->m_frameLenPadded, this->m_useHtkMethod ? "yes" : "no"); return std::string{strC}; } MFCC::MFCC(const MfccParams& params): _m_params(params), _m_filterBankInitialised(false) { this->_m_buffer = std::vector( this->_m_params.m_frameLenPadded, 0.0); this->_m_frame = std::vector( this->_m_params.m_frameLenPadded, 0.0); this->_m_melEnergies = std::vector( this->_m_params.m_numFbankBins, 0.0); this->_m_windowFunc = std::vector(this->_m_params.m_frameLen); const float multiplier = 2 * M_PI / this->_m_params.m_frameLen; /* Create window function. */ for (size_t i = 0; i < this->_m_params.m_frameLen; i++) { this->_m_windowFunc[i] = (0.5 - (0.5 * cos(static_cast(i) * multiplier))); } } void MFCC::Init() { this->_InitMelFilterBank(); } float MFCC::MelScale(const float freq, const bool useHTKMethod) { if (useHTKMethod) { return 1127.0f * logf (1.0f + freq / 700.0f); } else { /* Slaney formula for mel scale. */ float mel = freq / freqStep; if (freq >= minLogHz) { mel = minLogMel + logf(freq / minLogHz) / logStep; } return mel; } } float MFCC::InverseMelScale(const float melFreq, const bool useHTKMethod) { if (useHTKMethod) { return 700.0f * (expf (melFreq / 1127.0f) - 1.0f); } else { /* Slaney formula for mel scale. */ float freq = freqStep * melFreq; if (melFreq >= minLogMel) { freq = minLogHz * expf(logStep * (melFreq - minLogMel)); } return freq; } } bool MFCC::ApplyMelFilterBank( std::vector& fftVec, std::vector>& melFilterBank, std::vector& filterBankFilterFirst, std::vector& filterBankFilterLast, std::vector& melEnergies) { const size_t numBanks = melEnergies.size(); if (numBanks != filterBankFilterFirst.size() || numBanks != filterBankFilterLast.size()) { printf("unexpected filter bank lengths\n"); return false; } for (size_t bin = 0; bin < numBanks; ++bin) { auto filterBankIter = melFilterBank[bin].begin(); float melEnergy = 1e-10; /* Avoid log of zero at later stages */ const int32_t firstIndex = filterBankFilterFirst[bin]; const int32_t lastIndex = filterBankFilterLast[bin]; for (int32_t i = firstIndex; i <= lastIndex; ++i) { melEnergy += (*filterBankIter++ * fftVec[i]); } melEnergies[bin] = melEnergy; } return true; } void MFCC::ConvertToLogarithmicScale(std::vector& melEnergies) { float maxMelEnergy = -FLT_MAX; /* Container for natural logarithms of mel energies */ std::vector vecLogEnergies(melEnergies.size(), 0.f); /* Because we are taking natural logs, we need to multiply by log10(e). * Also, for wav2letter model, we scale our log10 values by 10 */ constexpr float multiplier = 10.0 * /* default scalar */ 0.4342944819032518; /* log10f(std::exp(1.0))*/ /* Take log of the whole vector */ MathUtils::VecLogarithmF32(melEnergies, vecLogEnergies); /* Scale the log values and get the max */ for (auto iterM = melEnergies.begin(), iterL = vecLogEnergies.begin(); iterM != melEnergies.end(); ++iterM, ++iterL) { *iterM = *iterL * multiplier; /* Save the max mel energy. */ if (*iterM > maxMelEnergy) { maxMelEnergy = *iterM; } } /* Clamp the mel energies */ constexpr float maxDb = 80.0; const float clampLevelLowdB = maxMelEnergy - maxDb; for (auto iter = melEnergies.begin(); iter != melEnergies.end(); ++iter) { *iter = std::max(*iter, clampLevelLowdB); } } void MFCC::_ConvertToPowerSpectrum() { const uint32_t halfDim = this->_m_params.m_frameLenPadded / 2; /* Handle this special case. */ float firstEnergy = this->_m_buffer[0] * this->_m_buffer[0]; float lastEnergy = this->_m_buffer[1] * this->_m_buffer[1]; MathUtils::ComplexMagnitudeSquaredF32( this->_m_buffer.data(), this->_m_buffer.size(), this->_m_buffer.data(), this->_m_buffer.size()/2); this->_m_buffer[0] = firstEnergy; this->_m_buffer[halfDim] = lastEnergy; } std::vector MFCC::CreateDCTMatrix( const int32_t inputLength, const int32_t coefficientCount) { std::vector dctMatix(inputLength * coefficientCount); /* Orthonormal normalization. */ const float normalizerK0 = 2 * sqrt(1.0 / static_cast(4*inputLength)); const float normalizer = 2 * sqrt(1.0 / static_cast(2*inputLength)); const float angleIncr = M_PI/inputLength; float angle = angleIncr; /* we start using it at k = 1 loop */ /* First row of DCT will use normalizer K0 */ for (int32_t n = 0; n < inputLength; ++n) { dctMatix[n] = normalizerK0; } /* Second row (index = 1) onwards, we use standard normalizer */ for (int32_t k = 1, m = inputLength; k < coefficientCount; ++k, m += inputLength) { for (int32_t n = 0; n < inputLength; ++n) { dctMatix[m+n] = normalizer * cos((n + 0.5) * angle); } angle += angleIncr; } return dctMatix; } float MFCC::GetMelFilterBankNormaliser( const float& leftMel, const float& rightMel, const bool useHTKMethod) { /* Slaney normalization for mel weights. */ return (2.0f / (MFCC::InverseMelScale(rightMel, useHTKMethod) - MFCC::InverseMelScale(leftMel, useHTKMethod))); } void MFCC::_InitMelFilterBank() { if (!this->_IsMelFilterBankInited()) { this->_m_melFilterBank = this->_CreateMelFilterBank(); this->_m_dctMatrix = this->CreateDCTMatrix( this->_m_params.m_numFbankBins, this->_m_params.m_numMfccFeatures); this->_m_filterBankInitialised = true; } } bool MFCC::_IsMelFilterBankInited() { return this->_m_filterBankInitialised; } void MFCC::_MfccComputePreFeature(const std::vector& audioData) { this->_InitMelFilterBank(); /* TensorFlow way of normalizing .wav data to (-1, 1). */ constexpr float normaliser = 1.0; for (size_t i = 0; i < this->_m_params.m_frameLen; i++) { this->_m_frame[i] = static_cast(audioData[i]) * normaliser; } /* Apply window function to input frame. */ for(size_t i = 0; i < this->_m_params.m_frameLen; i++) { this->_m_frame[i] *= this->_m_windowFunc[i]; } /* Set remaining frame values to 0. */ std::fill(this->_m_frame.begin() + this->_m_params.m_frameLen,this->_m_frame.end(), 0); /* Compute FFT. */ MathUtils::FftF32(this->_m_frame, this->_m_buffer); /* Convert to power spectrum. */ this->_ConvertToPowerSpectrum(); /* Apply mel filterbanks. */ if (!this->ApplyMelFilterBank(this->_m_buffer, this->_m_melFilterBank, this->_m_filterBankFilterFirst, this->_m_filterBankFilterLast, this->_m_melEnergies)) { printf("Failed to apply MEL filter banks\n"); } /* Convert to logarithmic scale */ this->ConvertToLogarithmicScale(this->_m_melEnergies); } std::vector MFCC::MfccCompute(const std::vector& audioData) { this->_MfccComputePreFeature(audioData); std::vector mfccOut(this->_m_params.m_numMfccFeatures); float * ptrMel = this->_m_melEnergies.data(); float * ptrDct = this->_m_dctMatrix.data(); float * ptrMfcc = mfccOut.data(); /* Take DCT. Uses matrix mul. */ for (size_t i = 0, j = 0; i < mfccOut.size(); ++i, j += this->_m_params.m_numFbankBins) { *ptrMfcc++ = MathUtils::DotProductF32( ptrDct + j, ptrMel, this->_m_params.m_numFbankBins); } return mfccOut; } std::vector> MFCC::_CreateMelFilterBank() { size_t numFftBins = this->_m_params.m_frameLenPadded / 2; float fftBinWidth = static_cast(this->_m_params.m_samplingFreq) / this->_m_params.m_frameLenPadded; float melLowFreq = MFCC::MelScale(this->_m_params.m_melLoFreq, this->_m_params.m_useHtkMethod); float melHighFreq = MFCC::MelScale(this->_m_params.m_melHiFreq, this->_m_params.m_useHtkMethod); float melFreqDelta = (melHighFreq - melLowFreq) / (this->_m_params.m_numFbankBins + 1); std::vector thisBin = std::vector(numFftBins); std::vector> melFilterBank( this->_m_params.m_numFbankBins); this->_m_filterBankFilterFirst = std::vector(this->_m_params.m_numFbankBins); this->_m_filterBankFilterLast = std::vector(this->_m_params.m_numFbankBins); for (size_t bin = 0; bin < this->_m_params.m_numFbankBins; bin++) { float leftMel = melLowFreq + bin * melFreqDelta; float centerMel = melLowFreq + (bin + 1) * melFreqDelta; float rightMel = melLowFreq + (bin + 2) * melFreqDelta; int32_t firstIndex = -1; int32_t lastIndex = -1; const float normaliser = this->GetMelFilterBankNormaliser(leftMel, rightMel, this->_m_params.m_useHtkMethod); for (size_t i = 0; i < numFftBins; i++) { float freq = (fftBinWidth * i); /* Center freq of this fft bin. */ float mel = MFCC::MelScale(freq, this->_m_params.m_useHtkMethod); thisBin[i] = 0.0; if (mel > leftMel && mel < rightMel) { float weight; if (mel <= centerMel) { weight = (mel - leftMel) / (centerMel - leftMel); } else { weight = (rightMel - mel) / (rightMel - centerMel); } thisBin[i] = weight * normaliser; if (firstIndex == -1) { firstIndex = i; } lastIndex = i; } } this->_m_filterBankFilterFirst[bin] = firstIndex; this->_m_filterBankFilterLast[bin] = lastIndex; /* Copy the part we care about. */ for (int32_t i = firstIndex; i <= lastIndex; i++) { melFilterBank[bin].push_back(thisBin[i]); } } return melFilterBank; }