/*
* _______ _____ _____ _____
* |__ __| | __ \ / ____| __ \
* | | __ _ _ __ ___ ___ ___| | | | (___ | |__) |
* | |/ _` | '__/ __|/ _ \/ __| | | |\___ \| ___/
* | | (_| | | \__ \ (_) \__ \ |__| |____) | |
* |_|\__,_|_| |___/\___/|___/_____/|_____/|_|
*
* -------------------------------------------------------------
*
* TarsosDSP is developed by Joren Six at IPEM, University Ghent
*
* -------------------------------------------------------------
*
* Info: http://0110.be/tag/TarsosDSP
* Github: https://github.com/JorenSix/TarsosDSP
* Releases: http://0110.be/releases/TarsosDSP/
*
* TarsosDSP includes modified source code by various authors,
* for credits and info, see README.
*
*/
package be.tarsos.dsp.pitch;
import be.tarsos.dsp.AudioEvent;
import be.tarsos.dsp.AudioProcessor;
/**
* Is responsible to call a pitch estimation algorithm. It also calculates progress.
* The underlying pitch detection algorithm must implement the {@link PitchDetector} interface.
* @author Joren Six
*/
public class PitchProcessor implements AudioProcessor {
/**
* A list of pitch estimation algorithms.
* @author Joren Six
*/
public enum PitchEstimationAlgorithm {
/**
* See {@link Yin} for the implementation. Or see <a href=
* "http://recherche.ircam.fr/equipes/pcm/cheveign/ps/2002_JASA_YIN_proof.pdf"
* >the YIN article</a>.
*/
YIN,
/**
* See {@link McLeodPitchMethod}. It is described in the article "<a
* href=
* "http://miracle.otago.ac.nz/postgrads/tartini/papers/A_Smarter_Way_to_Find_Pitch.pdf"
* >A Smarter Way to Find Pitch</a>".
*/
MPM,
/**
* A YIN implementation with a faster {@link FastYin} for the implementation. Or see <a href=
* "http://recherche.ircam.fr/equipes/pcm/cheveign/ps/2002_JASA_YIN_proof.pdf"
* >the YIN article</a>.
*/
FFT_YIN,
/**
* An implementation of a dynamic wavelet pitch detection algorithm (See
* {@link DynamicWavelet}), described in a paper by Eric Larson and Ross
* Maddox <a href= http://online.physics.uiuc
* .edu/courses/phys498pom/NSF_REU_Reports/2005_reu/Real
* -Time_Time-Domain_Pitch_Tracking_Using_Wavelets.pdf">"Real-Time
* Time-Domain Pitch Tracking Using Wavelets</a>
*/
DYNAMIC_WAVELET,
/**
* Returns the frequency of the FFT-bin with most energy.
*/
FFT_PITCH,
/**
* A pitch extractor that extracts the Average Magnitude Difference
* (AMDF) from an audio buffer. This is a good measure of the Pitch (f0)
* of a signal.
*/
AMDF;
/**
* Returns a new instance of a pitch detector object based on the provided values.
* @param sampleRate The sample rate of the audio buffer.
* @param bufferSize The size (in samples) of the audio buffer.
* @return A new pitch detector object.
*/
public PitchDetector getDetector(float sampleRate,int bufferSize){
PitchDetector detector;
if (this == MPM ) {
detector = new McLeodPitchMethod(sampleRate, bufferSize);
} else if(this == DYNAMIC_WAVELET ) {
detector = new DynamicWavelet(sampleRate,bufferSize);
} else if(this == FFT_YIN){
detector = new FastYin(sampleRate, bufferSize);
} else if(this==AMDF){
detector = new AMDF(sampleRate, bufferSize);
} else if (this == FFT_PITCH){
detector = new FFTPitch(Math.round(sampleRate),bufferSize);
} else {
detector = new Yin(sampleRate, bufferSize);
}
return detector;
}
};
/**
* The underlying pitch detector;
*/
private final PitchDetector detector;
private final PitchDetectionHandler handler;
/**
* Initialize a new pitch processor.
*
* @param algorithm
* An enum defining the algorithm.
* @param sampleRate
* The sample rate of the buffer (Hz).
* @param bufferSize
* The size of the buffer in samples.
* @param handler
* The handler handles detected pitch.
*/
public PitchProcessor(PitchEstimationAlgorithm algorithm, float sampleRate,
int bufferSize,
PitchDetectionHandler handler) {
detector = algorithm.getDetector(sampleRate, bufferSize);
this.handler = handler;
}
@Override
public boolean process(AudioEvent audioEvent) {
float[] audioFloatBuffer = audioEvent.getFloatBuffer();
PitchDetectionResult result = detector.getPitch(audioFloatBuffer);
handler.handlePitch(result,audioEvent);
return true;
}
@Override
public void processingFinished() {
}
}