Description |
The BeatDetect class allows you to analyze an audio stream for beats (rhythmic onsets).
Beat
Detection Algorithms by Frederic Patin describes beats in the following
way: The human listening system determines the rhythm of music
by detecting a pseudo periodical succession of beats. The signal which is
intercepted by the ear contains a certain energy, this energy is converted
into an electrical signal which the brain interprets. Obviously, The more
energy the sound transports, the louder the sound will seem. But a sound will
be heard as a beat only if his energy is largely superior to the
sound's energy history, that is to say if the brain detects a
brutal variation in sound energy. Therefore if the ear intercepts
a monotonous sound with sometimes big energy peaks it will detect beats,
however, if you play a continuous loud sound you will not perceive any beats.
Thus, the beats are big variations of sound energy. In fact,
the two algorithms in this class are based on two algorithms described in
that paper.
To use this class, inside of draw() you must first call
detect() , passing the AudioBuffer you want to
analyze. You may then use the isXXX functions to find out what
beats have occurred in that frame. For example, you might use
isKick() to cause a circle to pulse.
BeatDetect has two modes: sound energy tracking and frequency energy
tracking. In sound energy mode, the level of the buffer, as returned by
level() , is used as the instant energy in each frame. Beats,
then, are spikes in this value, relative to the previous one second of sound.
In frequency energy mode, the same process is used but instead of tracking
the level of the buffer, an FFT is used to obtain a spectrum, which is then
divided into average bands using logAverages() , and each of
these bands is tracked individually. The result is that it is possible to
track sounds that occur in different parts of the frequency spectrum
independently (like the kick drum and snare drum).
In sound energy mode you use isOnset() to query the algorithm
and in frequency energy mode you use isOnset(int i) ,
isKick() , isSnare() , and
isRange() to query particular frequnecy bands or ranges of
frequency bands. It should be noted that isKick() ,
isSnare() , and isHat() merely call
isRange() with values determined by testing the algorithm
against music with a heavy beat and they may not be appropriate for all kinds
of music. If you find they are performing poorly with your music, you should
use isRange() directly to locate the bands that provide the
most meaningful information for you. |
Examples |
/**
* This sketch demonstrates how to use the BeatDetect object song SOUND_ENERGY mode.<br />
* You must call <code>detect</code> every frame and then you can use <code>isOnset</code>
* to track the beat of the music.
* <p>
* This sketch plays an entire song, so it may be a little slow to load.
* <p>
* For more information about Minim and additional features,
* visit http://code.compartmental.net/minim/
*/
import ddf.minim.*;
import ddf.minim.analysis.*;
Minim minim;
AudioPlayer song;
BeatDetect beat;
float eRadius;
void setup()
{
size(200, 200, P3D);
minim = new Minim(this);
song = minim.loadFile("marcus_kellis_theme.mp3", 2048);
song.play();
// a beat detection object song SOUND_ENERGY mode with a sensitivity of 10 milliseconds
beat = new BeatDetect();
ellipseMode(RADIUS);
eRadius = 20;
}
void draw()
{
background(0);
beat.detect(song.mix);
float a = map(eRadius, 20, 80, 60, 255);
fill(60, 255, 0, a);
if ( beat.isOnset() ) eRadius = 80;
ellipse(width/2, height/2, eRadius, eRadius);
eRadius *= 0.95;
if ( eRadius < 20 ) eRadius = 20;
}
|
Methods |
detect ( ) |
|
Analyze the samples in buffer .
This is a cumulative process, so you must call this function every frame.
|
detectMode ( ) |
|
Set the object to use the requested algorithm. If an invalid value is
passed, the function will report and error and default to
BeatDetect.SOUND_ENERGY
|
detectSize ( ) |
|
In frequency energy mode this returns the number of frequency bands
currently being used. In sound energy mode this always returns 0.
|
getDetectCenterFrequency ( ) |
|
Returns the center frequency of the ith frequency band.
In sound energy mode this always returns 0.
|
isHat ( ) |
|
In frequency energy mode this returns true if a beat corresponding to the
frequency range of a hi hat has been detected. This has been tuned to work
well with dance / techno music and may not perform well with other styles
of music. In sound energy mode this always returns false.
|
isKick ( ) |
|
In frequency energy mode this returns true if a beat corresponding to the
frequency range of a kick drum has been detected. This has been tuned to
work well with dance / techno music and may not perform well with other
styles of music. In sound energy mode this always returns false.
|
isOnset ( ) |
|
In sound energy mode this returns true when a beat has been detected. In
frequency energy mode this always returns false.
|
isRange ( ) |
|
In frequency energy mode this returns true if at least
threshold bands of the bands included in the range
[low, high] have registered a beat. In sound energy mode
this always returns false.
|
isSnare ( ) |
|
In frequency energy mode this returns true if a beat corresponding to the
frequency range of a snare drum has been detected. This has been tuned to
work well with dance / techno music and may not perform well with other
styles of music. In sound energy mode this always returns false.
|
setSensitivity ( ) |
|
Sets the sensitivity of the algorithm. After a beat has been detected, the
algorithm will wait for millis milliseconds before allowing
another beat to be reported. You can use this to dampen the algorithm if
it is giving too many false-positives. The default value is 10, which is
essentially no damping. If you try to set the sensitivity to a negative
value, an error will be reported and it will be set to 10 instead.
|
|