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