dolphin/Externals/soundtouch/BPMDetect.cpp

571 lines
17 KiB
C++

////////////////////////////////////////////////////////////////////////////////
///
/// Beats-per-minute (BPM) detection routine.
///
/// The beat detection algorithm works as follows:
/// - Use function 'inputSamples' to input a chunks of samples to the class for
/// analysis. It's a good idea to enter a large sound file or stream in smallish
/// chunks of around few kilosamples in order not to extinguish too much RAM memory.
/// - Inputted sound data is decimated to approx 500 Hz to reduce calculation burden,
/// which is basically ok as low (bass) frequencies mostly determine the beat rate.
/// Simple averaging is used for anti-alias filtering because the resulting signal
/// quality isn't of that high importance.
/// - Decimated sound data is enveloped, i.e. the amplitude shape is detected by
/// taking absolute value that's smoothed by sliding average. Signal levels that
/// are below a couple of times the general RMS amplitude level are cut away to
/// leave only notable peaks there.
/// - Repeating sound patterns (e.g. beats) are detected by calculating short-term
/// autocorrelation function of the enveloped signal.
/// - After whole sound data file has been analyzed as above, the bpm level is
/// detected by function 'getBpm' that finds the highest peak of the autocorrelation
/// function, calculates it's precise location and converts this reading to bpm's.
///
/// Author : Copyright (c) Olli Parviainen
/// Author e-mail : oparviai 'at' iki.fi
/// SoundTouch WWW: http://www.surina.net/soundtouch
///
////////////////////////////////////////////////////////////////////////////////
//
// License :
//
// SoundTouch audio processing library
// Copyright (c) Olli Parviainen
//
// This library is free software; you can redistribute it and/or
// modify it under the terms of the GNU Lesser General Public
// License as published by the Free Software Foundation; either
// version 2.1 of the License, or (at your option) any later version.
//
// This library is distributed in the hope that it will be useful,
// but WITHOUT ANY WARRANTY; without even the implied warranty of
// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
// Lesser General Public License for more details.
//
// You should have received a copy of the GNU Lesser General Public
// License along with this library; if not, write to the Free Software
// Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA
//
////////////////////////////////////////////////////////////////////////////////
#include <math.h>
#include <assert.h>
#include <string.h>
#include <stdio.h>
#include <cfloat>
#include "FIFOSampleBuffer.h"
#include "PeakFinder.h"
#include "BPMDetect.h"
using namespace soundtouch;
// algorithm input sample block size
static const int INPUT_BLOCK_SIZE = 2048;
// decimated sample block size
static const int DECIMATED_BLOCK_SIZE = 256;
/// Target sample rate after decimation
static const int TARGET_SRATE = 1000;
/// XCorr update sequence size, update in about 200msec chunks
static const int XCORR_UPDATE_SEQUENCE = (int)(TARGET_SRATE / 5);
/// Moving average N size
static const int MOVING_AVERAGE_N = 15;
/// XCorr decay time constant, decay to half in 30 seconds
/// If it's desired to have the system adapt quicker to beat rate
/// changes within a continuing music stream, then the
/// 'xcorr_decay_time_constant' value can be reduced, yet that
/// can increase possibility of glitches in bpm detection.
static const double XCORR_DECAY_TIME_CONSTANT = 30.0;
/// Data overlap factor for beat detection algorithm
static const int OVERLAP_FACTOR = 4;
#define PI 3.14159265358979323846
#define TWOPI (2 * PI)
////////////////////////////////////////////////////////////////////////////////
// Enable following define to create bpm analysis file:
//#define _CREATE_BPM_DEBUG_FILE
#ifdef _CREATE_BPM_DEBUG_FILE
static void _SaveDebugData(const char *name, const float *data, int minpos, int maxpos, double coeff)
{
FILE *fptr = fopen(name, "wt");
int i;
if (fptr)
{
printf("\nWriting BPM debug data into file %s\n", name);
for (i = minpos; i < maxpos; i ++)
{
fprintf(fptr, "%d\t%.1lf\t%f\n", i, coeff / (double)i, data[i]);
}
fclose(fptr);
}
}
void _SaveDebugBeatPos(const char *name, const std::vector<BEAT> &beats)
{
printf("\nWriting beat detections data into file %s\n", name);
FILE *fptr = fopen(name, "wt");
if (fptr)
{
for (uint i = 0; i < beats.size(); i++)
{
BEAT b = beats[i];
fprintf(fptr, "%lf\t%lf\n", b.pos, b.strength);
}
fclose(fptr);
}
}
#else
#define _SaveDebugData(name, a,b,c,d)
#define _SaveDebugBeatPos(name, b)
#endif
// Hamming window
void hamming(float *w, int N)
{
for (int i = 0; i < N; i++)
{
w[i] = (float)(0.54 - 0.46 * cos(TWOPI * i / (N - 1)));
}
}
////////////////////////////////////////////////////////////////////////////////
//
// IIR2_filter - 2nd order IIR filter
IIR2_filter::IIR2_filter(const double *lpf_coeffs)
{
memcpy(coeffs, lpf_coeffs, 5 * sizeof(double));
memset(prev, 0, sizeof(prev));
}
float IIR2_filter::update(float x)
{
prev[0] = x;
double y = x * coeffs[0];
for (int i = 4; i >= 1; i--)
{
y += coeffs[i] * prev[i];
prev[i] = prev[i - 1];
}
prev[3] = y;
return (float)y;
}
// IIR low-pass filter coefficients, calculated with matlab/octave cheby2(2,40,0.05)
const double _LPF_coeffs[5] = { 0.00996655391939, -0.01944529148401, 0.00996655391939, 1.96867605796247, -0.96916387431724 };
////////////////////////////////////////////////////////////////////////////////
BPMDetect::BPMDetect(int numChannels, int aSampleRate) :
beat_lpf(_LPF_coeffs)
{
beats.reserve(250); // initial reservation to prevent frequent reallocation
this->sampleRate = aSampleRate;
this->channels = numChannels;
decimateSum = 0;
decimateCount = 0;
// choose decimation factor so that result is approx. 1000 Hz
decimateBy = sampleRate / TARGET_SRATE;
if ((decimateBy <= 0) || (decimateBy * DECIMATED_BLOCK_SIZE < INPUT_BLOCK_SIZE))
{
ST_THROW_RT_ERROR("Too small samplerate");
}
// Calculate window length & starting item according to desired min & max bpms
windowLen = (60 * sampleRate) / (decimateBy * MIN_BPM);
windowStart = (60 * sampleRate) / (decimateBy * MAX_BPM_RANGE);
assert(windowLen > windowStart);
// allocate new working objects
xcorr = new float[windowLen];
memset(xcorr, 0, windowLen * sizeof(float));
pos = 0;
peakPos = 0;
peakVal = 0;
init_scaler = 1;
beatcorr_ringbuffpos = 0;
beatcorr_ringbuff = new float[windowLen];
memset(beatcorr_ringbuff, 0, windowLen * sizeof(float));
// allocate processing buffer
buffer = new FIFOSampleBuffer();
// we do processing in mono mode
buffer->setChannels(1);
buffer->clear();
// calculate hamming windows
hamw = new float[XCORR_UPDATE_SEQUENCE];
hamming(hamw, XCORR_UPDATE_SEQUENCE);
hamw2 = new float[XCORR_UPDATE_SEQUENCE / 2];
hamming(hamw2, XCORR_UPDATE_SEQUENCE / 2);
}
BPMDetect::~BPMDetect()
{
delete[] xcorr;
delete[] beatcorr_ringbuff;
delete[] hamw;
delete[] hamw2;
delete buffer;
}
/// convert to mono, low-pass filter & decimate to about 500 Hz.
/// return number of outputted samples.
///
/// Decimation is used to remove the unnecessary frequencies and thus to reduce
/// the amount of data needed to be processed as calculating autocorrelation
/// function is a very-very heavy operation.
///
/// Anti-alias filtering is done simply by averaging the samples. This is really a
/// poor-man's anti-alias filtering, but it's not so critical in this kind of application
/// (it'd also be difficult to design a high-quality filter with steep cut-off at very
/// narrow band)
int BPMDetect::decimate(SAMPLETYPE *dest, const SAMPLETYPE *src, int numsamples)
{
int count, outcount;
LONG_SAMPLETYPE out;
assert(channels > 0);
assert(decimateBy > 0);
outcount = 0;
for (count = 0; count < numsamples; count ++)
{
int j;
// convert to mono and accumulate
for (j = 0; j < channels; j ++)
{
decimateSum += src[j];
}
src += j;
decimateCount ++;
if (decimateCount >= decimateBy)
{
// Store every Nth sample only
out = (LONG_SAMPLETYPE)(decimateSum / (decimateBy * channels));
decimateSum = 0;
decimateCount = 0;
#ifdef SOUNDTOUCH_INTEGER_SAMPLES
// check ranges for sure (shouldn't actually be necessary)
if (out > 32767)
{
out = 32767;
}
else if (out < -32768)
{
out = -32768;
}
#endif // SOUNDTOUCH_INTEGER_SAMPLES
dest[outcount] = (SAMPLETYPE)out;
outcount ++;
}
}
return outcount;
}
// Calculates autocorrelation function of the sample history buffer
void BPMDetect::updateXCorr(int process_samples)
{
int offs;
SAMPLETYPE *pBuffer;
assert(buffer->numSamples() >= (uint)(process_samples + windowLen));
assert(process_samples == XCORR_UPDATE_SEQUENCE);
pBuffer = buffer->ptrBegin();
// calculate decay factor for xcorr filtering
float xcorr_decay = (float)pow(0.5, 1.0 / (XCORR_DECAY_TIME_CONSTANT * TARGET_SRATE / process_samples));
// prescale pbuffer
float tmp[XCORR_UPDATE_SEQUENCE];
for (int i = 0; i < process_samples; i++)
{
tmp[i] = hamw[i] * hamw[i] * pBuffer[i];
}
#pragma omp parallel for
for (offs = windowStart; offs < windowLen; offs ++)
{
float sum;
int i;
sum = 0;
for (i = 0; i < process_samples; i ++)
{
sum += tmp[i] * pBuffer[i + offs]; // scaling the sub-result shouldn't be necessary
}
xcorr[offs] *= xcorr_decay; // decay 'xcorr' here with suitable time constant.
xcorr[offs] += (float)fabs(sum);
}
}
// Detect individual beat positions
void BPMDetect::updateBeatPos(int process_samples)
{
SAMPLETYPE *pBuffer;
assert(buffer->numSamples() >= (uint)(process_samples + windowLen));
pBuffer = buffer->ptrBegin();
assert(process_samples == XCORR_UPDATE_SEQUENCE / 2);
// static double thr = 0.0003;
double posScale = (double)this->decimateBy / (double)this->sampleRate;
int resetDur = (int)(0.12 / posScale + 0.5);
// prescale pbuffer
float tmp[XCORR_UPDATE_SEQUENCE / 2];
for (int i = 0; i < process_samples; i++)
{
tmp[i] = hamw2[i] * hamw2[i] * pBuffer[i];
}
#pragma omp parallel for
for (int offs = windowStart; offs < windowLen; offs++)
{
float sum = 0;
for (int i = 0; i < process_samples; i++)
{
sum += tmp[i] * pBuffer[offs + i];
}
beatcorr_ringbuff[(beatcorr_ringbuffpos + offs) % windowLen] += (float)((sum > 0) ? sum : 0); // accumulate only positive correlations
}
int skipstep = XCORR_UPDATE_SEQUENCE / OVERLAP_FACTOR;
// compensate empty buffer at beginning by scaling coefficient
float scale = (float)windowLen / (float)(skipstep * init_scaler);
if (scale > 1.0f)
{
init_scaler++;
}
else
{
scale = 1.0f;
}
// detect beats
for (int i = 0; i < skipstep; i++)
{
float sum = beatcorr_ringbuff[beatcorr_ringbuffpos];
sum -= beat_lpf.update(sum);
if (sum > peakVal)
{
// found new local largest value
peakVal = sum;
peakPos = pos;
}
if (pos > peakPos + resetDur)
{
// largest value not updated for 200msec => accept as beat
peakPos += skipstep;
if (peakVal > 0)
{
// add detected beat to end of "beats" vector
BEAT temp = { (float)(peakPos * posScale), (float)(peakVal * scale) };
beats.push_back(temp);
}
peakVal = 0;
peakPos = pos;
}
beatcorr_ringbuff[beatcorr_ringbuffpos] = 0;
pos++;
beatcorr_ringbuffpos = (beatcorr_ringbuffpos + 1) % windowLen;
}
}
#define max(x,y) ((x) > (y) ? (x) : (y))
void BPMDetect::inputSamples(const SAMPLETYPE *samples, int numSamples)
{
SAMPLETYPE decimated[DECIMATED_BLOCK_SIZE];
// iterate so that max INPUT_BLOCK_SAMPLES processed per iteration
while (numSamples > 0)
{
int block;
int decSamples;
block = (numSamples > INPUT_BLOCK_SIZE) ? INPUT_BLOCK_SIZE : numSamples;
// decimate. note that converts to mono at the same time
decSamples = decimate(decimated, samples, block);
samples += block * channels;
numSamples -= block;
buffer->putSamples(decimated, decSamples);
}
// when the buffer has enough samples for processing...
int req = max(windowLen + XCORR_UPDATE_SEQUENCE, 2 * XCORR_UPDATE_SEQUENCE);
while ((int)buffer->numSamples() >= req)
{
// ... update autocorrelations...
updateXCorr(XCORR_UPDATE_SEQUENCE);
// ...update beat position calculation...
updateBeatPos(XCORR_UPDATE_SEQUENCE / 2);
// ... and remove proceessed samples from the buffer
int n = XCORR_UPDATE_SEQUENCE / OVERLAP_FACTOR;
buffer->receiveSamples(n);
}
}
void BPMDetect::removeBias()
{
int i;
// Remove linear bias: calculate linear regression coefficient
// 1. calc mean of 'xcorr' and 'i'
double mean_i = 0;
double mean_x = 0;
for (i = windowStart; i < windowLen; i++)
{
mean_x += xcorr[i];
}
mean_x /= (windowLen - windowStart);
mean_i = 0.5 * (windowLen - 1 + windowStart);
// 2. calculate linear regression coefficient
double b = 0;
double div = 0;
for (i = windowStart; i < windowLen; i++)
{
double xt = xcorr[i] - mean_x;
double xi = i - mean_i;
b += xt * xi;
div += xi * xi;
}
b /= div;
// subtract linear regression and resolve min. value bias
float minval = FLT_MAX; // arbitrary large number
for (i = windowStart; i < windowLen; i ++)
{
xcorr[i] -= (float)(b * i);
if (xcorr[i] < minval)
{
minval = xcorr[i];
}
}
// subtract min.value
for (i = windowStart; i < windowLen; i ++)
{
xcorr[i] -= minval;
}
}
// Calculate N-point moving average for "source" values
void MAFilter(float *dest, const float *source, int start, int end, int N)
{
for (int i = start; i < end; i++)
{
int i1 = i - N / 2;
int i2 = i + N / 2 + 1;
if (i1 < start) i1 = start;
if (i2 > end) i2 = end;
double sum = 0;
for (int j = i1; j < i2; j ++)
{
sum += source[j];
}
dest[i] = (float)(sum / (i2 - i1));
}
}
float BPMDetect::getBpm()
{
double peakPos;
double coeff;
PeakFinder peakFinder;
// remove bias from xcorr data
removeBias();
coeff = 60.0 * ((double)sampleRate / (double)decimateBy);
// save bpm debug data if debug data writing enabled
_SaveDebugData("soundtouch-bpm-xcorr.txt", xcorr, windowStart, windowLen, coeff);
// Smoothen by N-point moving-average
float *data = new float[windowLen];
memset(data, 0, sizeof(float) * windowLen);
MAFilter(data, xcorr, windowStart, windowLen, MOVING_AVERAGE_N);
// find peak position
peakPos = peakFinder.detectPeak(data, windowStart, windowLen);
// save bpm debug data if debug data writing enabled
_SaveDebugData("soundtouch-bpm-smoothed.txt", data, windowStart, windowLen, coeff);
delete[] data;
assert(decimateBy != 0);
if (peakPos < 1e-9) return 0.0; // detection failed.
_SaveDebugBeatPos("soundtouch-detected-beats.txt", beats);
// calculate BPM
float bpm = (float)(coeff / peakPos);
return (bpm >= MIN_BPM && bpm <= MAX_BPM_VALID) ? bpm : 0;
}
/// Get beat position arrays. Note: The array includes also really low beat detection values
/// in absence of clear strong beats. Consumer may wish to filter low values away.
/// - "pos" receive array of beat positions
/// - "values" receive array of beat detection strengths
/// - max_num indicates max.size of "pos" and "values" array.
///
/// You can query a suitable array sized by calling this with nullptr in "pos" & "values".
///
/// \return number of beats in the arrays.
int BPMDetect::getBeats(float *pos, float *values, int max_num)
{
int num = (int)beats.size();
if ((!pos) || (!values)) return num; // pos or values nullptr, return just size
for (int i = 0; (i < num) && (i < max_num); i++)
{
pos[i] = beats[i].pos;
values[i] = beats[i].strength;
}
return num;
}