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Introduction AM/FM analysis Smoothing/Resynthesis Psychoacoustic metrics Results Conclusions
Psychoacoustic impact assessment ofsmoothed AM/FM resonance signals
Antonio Goulart, Marcelo QueirozJoseph Timoney, Victor Lazzarini
Computer Music Research Group - IME/USP - BrazilSound and Digital Music Technology Group - NUIM - Ireland
SMC - 2015/07/31
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Introduction AM/FM analysis Smoothing/Resynthesis Psychoacoustic metrics Results Conclusions
Resonance
tendency of a system to vibrate sympathetically at a particularfrequency in response to energy induced at that frequency.
FOF, VOSIM, ModFM, Phase distortion
Analysis/resynthesis
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Introduction AM/FM analysis Smoothing/Resynthesis Psychoacoustic metrics Results Conclusions
TB-303
Resonance Env Mod Decay Label
60% max min A
60% max 60% B
max 75% 25% C
max 75% 75% D
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Introduction AM/FM analysis Smoothing/Resynthesis Psychoacoustic metrics Results Conclusions
Waveform D
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Introduction AM/FM analysis Smoothing/Resynthesis Psychoacoustic metrics Results Conclusions
x(t) = a(t) cos (θ(t))
θ(t) = f (t), instantaneous frequency => fits locallya(t), instantaneous amplitude
various techniquesHilbert Transform
x(t) = x(t) ∗ 1
πt90◦ phase shift => analytic signal
z(t) = x(t) + j x(t) = |z(t)|e jθ(t)
resynthesis
y(t) = a(t) cos
(∫ t
−∞f (τ)dτ
)5 / 21
Introduction AM/FM analysis Smoothing/Resynthesis Psychoacoustic metrics Results Conclusions
Decomposition - Waveform D - AM portion
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Introduction AM/FM analysis Smoothing/Resynthesis Psychoacoustic metrics Results Conclusions
Decomposition - Waveform D - FM portion
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Introduction AM/FM analysis Smoothing/Resynthesis Psychoacoustic metrics Results Conclusions
Boxcar windowHanning window20 and 100 samples longwindow w(t)
y(t) = (a ∗ w)(t) cos
(∫ t
−∞(f ∗ w)(τ)dτ
)
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Introduction AM/FM analysis Smoothing/Resynthesis Psychoacoustic metrics Results Conclusions
Comparison - AM portion - Smoothing with Boxcar 20
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Introduction AM/FM analysis Smoothing/Resynthesis Psychoacoustic metrics Results Conclusions
Comparison - FM portion - Smoothing with Boxcar 20
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Introduction AM/FM analysis Smoothing/Resynthesis Psychoacoustic metrics Results Conclusions
Brightness
center of gravity of the spectrumrelated to the most prominent portion of a spectrum(specially with resonant sounds)usually the metric that presents larger variations
Br =
N∑k=1
kak
N∑k=1
ak
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Introduction AM/FM analysis Smoothing/Resynthesis Psychoacoustic metrics Results Conclusions
Tristimulus
introduced as a timbre equivalent to the color attributes in vision
Tr1 =a1
N∑k=1
ak
Tr2 =(a2 + a3 + a4)
N∑k=1
ak
Tr3 =
N∑k=5
ak
N∑k=1
ak
related to the warmth (3.5)12 / 21
Introduction AM/FM analysis Smoothing/Resynthesis Psychoacoustic metrics Results Conclusions
Tristimulus
Tr1 + Tr2 + Tr3 = 1close to origin => strong fundamentalclose to right corner => strong high partialsclose to up corner => strong mid-range partials
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Introduction AM/FM analysis Smoothing/Resynthesis Psychoacoustic metrics Results Conclusions
Irregularity
jaggedness, ripples
Ir =
N∑k=1
(ak − ak+1)2
N∑k=1
a2k
, aN+1 = 0
square, clarinet => max irregularity => hollow soundimpulse train => zero irregularity => buzz
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Introduction AM/FM analysis Smoothing/Resynthesis Psychoacoustic metrics Results Conclusions
Brightness
Waveform A and C - AM/FM smoothing
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Introduction AM/FM analysis Smoothing/Resynthesis Psychoacoustic metrics Results Conclusions
Brightness
Waveform A - AM-only and FM-only smoothing
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Introduction AM/FM analysis Smoothing/Resynthesis Psychoacoustic metrics Results Conclusions
Tristimulus
Waveform A and C - AM/FM smoothing
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Introduction AM/FM analysis Smoothing/Resynthesis Psychoacoustic metrics Results Conclusions
Tristimulus
Waveform A - AM-only and FM-only smoothing
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Introduction AM/FM analysis Smoothing/Resynthesis Psychoacoustic metrics Results Conclusions
Irregularity
Waveform A and C - AM/FM smoothing
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Introduction AM/FM analysis Smoothing/Resynthesis Psychoacoustic metrics Results Conclusions
Irregularity
Waveform A - AM-only and FM-only smoothing
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Introduction AM/FM analysis Smoothing/Resynthesis Psychoacoustic metrics Results Conclusions
brightness/tristimulus point of view, not effective to smoothsignals with strong resonance(although it certainly changes the sound)
tristimulus more affected by smoothing the FM component
irregularity more affected by smoothing the AM component
more irregular input => more similar perceptual outcome
interesting variations when processing modest and mildresonances
longer smoothers => less artifacts
Hanning smoothers => less artifacts
suite of AM/FM effects
Thanks a [email protected]
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