Loudness: table of contents
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Loudness : UGen : AbstractFunction : Object

Extraction of instantaneous loudness in sones

Description

A perceptual loudness function which outputs loudness in sones; this is a variant of an MP3 perceptual model, summing excitation in ERB bands. It models simple spectral and temporal masking, with equal loudness contour correction in ERB bands to obtain phons (relative dB), then a phon to sone transform. The final output is typically in the range of 0 to 64 sones, though higher values can occur with specific synthesised stimuli.

NOTE: Research note: This UGen is an informal juxtaposition of perceptual coding, and a Zwicker and Glasberg/Moore/Stone loudness model.

Class Methods

Loudness.kr(chain, smask: 0.25, tmask: 1)

Arguments:

chain

[fft] Audio input to track, which has been pre-analysed by the FFT UGen; see examples below for the expected FFT size.

smask

[sk] Spectral masking param: lower bins mask higher bin power within ERB bands, with a power falloff (leaky integration multiplier) of smask per bin.

tmask

[sk] Temporal masking param: the phon level let through in an ERB band is the maximum of the new measurement, and the previous minus tmask phons.

Inherited class methods

Instance Methods

Inherited instance methods

Examples

// assumes hop of half fftsize, fine

d = Buffer.read(s, Platform.resourceDir +/+ "sounds/a11wlk01.wav");

// analyse loudness and poll result
(
{
    var in = PlayBuf.ar(1, d, BufRateScale.kr(d), 1, 0, 1);
    var chain = FFT(LocalBuf(1024), in);  // for sampling rates 44100 and 48000
    //var chain = FFT(LocalBuf(2048), in);  // for sampling rates 88200 and 96000
    var loudness = Loudness.kr(chain).poll(50);
    Pan2.ar(in)
}.play
)


// TESTS
// sones = 2 ** ((phon - 40) / 10)
// sine of 40 dB = 40 phon at 1000 kHz = 1 sone
// full amp = 100 dB
// -60.dbamp = 0.001 = 1 sone
// -40.dbamp = 0.01 = 4 sone
// -20.dbamp= 0.1 = 16 sone
// 0.dbamp= 1 = 64 sone
(
{
    var in, chain, loudness;

    in = SinOsc.ar(1000, 0, 0.001); //should be 1 sone
    //in = SinOsc.ar(1000, 0, 0.01); //should be 4 sone
    //in = SinOsc.ar(1000, 0, 0.1); //should be 16 sone
    //in = SinOsc.ar(1000, 0, 1); //should be 64 sone
    //in = Saw.ar * SinOsc.ar(4);
    //in = WhiteNoise.ar;
    //in = Silent.ar; // should be small, around 2 ** ((0 - 40) / 10) = 2 ** (-4) = 0.0625
    //in = DC.ar(1);
    //in = SinOsc.ar(22050, pi * 0.5, 1);
    // fade ins
    //in = SinOsc.ar(1000, 0, Line.kr(0, 1, 2));
    //in = SinOsc.ar(1000, 0, Line.kr(0, 1, 2) ** 2);
    //in = WhiteNoise.ar(Line.kr(0, 1, 2));
    //in = PlayBuf.ar(1, d, BufRateScale.kr(d), 1, 0, 1);

    chain = FFT(LocalBuf(1024), in);  // for sampling rates 44100 and 48000
    //chain = FFT(LocalBuf(2048), in);  // for sampling rates 88200 and 96000

    loudness = Loudness.kr(chain, 0.25, 6).poll(50);

    K2A.ar(loudness * 0.016)
}.plot(2.0)
)