blob: 234b14d3befe96c4eba27650e0c2208f47cb853f [file] [log] [blame]
//
// Copyright © 2020 Arm Ltd and Contributors. All rights reserved.
// SPDX-License-Identifier: MIT
//
#include <cstdio>
#include <float.h>
#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<float>(
this->_m_params.m_frameLenPadded, 0.0);
this->_m_frame = std::vector<float>(
this->_m_params.m_frameLenPadded, 0.0);
this->_m_melEnergies = std::vector<float>(
this->_m_params.m_numFbankBins, 0.0);
this->_m_windowFunc = std::vector<float>(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<float>(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<float>& fftVec,
std::vector<std::vector<float>>& melFilterBank,
std::vector<int32_t>& filterBankFilterFirst,
std::vector<int32_t>& filterBankFilterLast,
std::vector<float>& 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<float>& melEnergies)
{
float maxMelEnergy = -FLT_MAX;
/* Container for natural logarithms of mel energies */
std::vector <float> 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<float> MFCC::CreateDCTMatrix(
const int32_t inputLength,
const int32_t coefficientCount)
{
std::vector<float> dctMatix(inputLength * coefficientCount);
/* Orthonormal normalization. */
const float normalizerK0 = 2 * sqrt(1.0 / static_cast<float>(4*inputLength));
const float normalizer = 2 * sqrt(1.0 / static_cast<float>(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<float>& 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<float>(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<float> MFCC::MfccCompute(const std::vector<float>& audioData)
{
this->_MfccComputePreFeature(audioData);
std::vector<float> 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<std::vector<float>> MFCC::_CreateMelFilterBank()
{
size_t numFftBins = this->_m_params.m_frameLenPadded / 2;
float fftBinWidth = static_cast<float>(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<float> thisBin = std::vector<float>(numFftBins);
std::vector<std::vector<float>> melFilterBank(
this->_m_params.m_numFbankBins);
this->_m_filterBankFilterFirst =
std::vector<int32_t>(this->_m_params.m_numFbankBins);
this->_m_filterBankFilterLast =
std::vector<int32_t>(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;
}