Real-time Spectral Attenuation Based Analysis and
Resynthesis, Spectral Modification, Spectral Accumulation,
and Spectral Evaporation; Theory, Implementation, and
Compositional Implications.
Ronald Keith Parks, Ph.D., Winthrop University (parksr@winthrop.edu)
Abstract: Building upon convolution-based EQ (Settel and Lippe 1997 rev. 2001) spectral analysis data is utilized to
attenuate FFT bins (derived from an FFT analysis of noise) to create an FFT/IFFT-based subtractive analysis/resynthesis
module. Techniques for modification of analysis data prior to resynthesis, producing a variety of effects, are examined and
demonstrated. Methods for retaining information from previous analysis (spectral accumulation) and for systematic data
attrition (spectral evaporation) are introduced. A MaxMSP graphic user interface, designed by the author for implementation
of the techniques, is discussed and described. Compositional implications are examined and musical examples are utilized to
illustrate potential musical applications.
t
1. Spectral Attenuation-Based Analysis and Resynthesis.
techniques for modification of analysis data prior to
resynthesis.
Building upon the analysis/oscillator bank
approach to analysis/resynthesis, attenuation based
analysis/resynthesis also employs Fourier analysis of the
original audio signal to obtain the frequency and amplitude
of the most significant peaks in the harmonic spectrum. In
the current implementation analysis is achieved via the
MaxMSP fiddle- object' (Puckette, 1998; MSP port by Ted
Apel, David Zicarelli). The incoming audio is analyzed and
fiddle- is configured to report the relative amplitude of the
thirty-two most significant spectral peaks as determined by
the analysis. This information is output from fiddle- as a list
of numbers for each reported spectral peak. The list includes
the index number (or partial number), the frequency of the
spectral peak in hertz, and the relative amplitude of each
spectral peak. At this point in the process, attenuation based
analysis/resynthesis departs from previous approaches in
that the frequency and amplitude data are stored as sample
values at pre-determined locations in a buffer (hereafter
referred to as the spectral index) instead of being passed on
to an oscillator bank. Each sample location in the spectral
index corresponds to an FFT frequency bin of a
predetermined size. The spectral index address for a given
frequency can be determined by f/(sr/FFT-size) where f is
the frequency in Hertz, sr is the sampling rate, and FFT-size
is the size of the FFT in samples. Resynthesis is achieved by
performing a Fourier analysis of white noise, then
attenuating each frequency bin of the FFT output by
multiplying it by the value reported by the analysis module,
and stored in the spectral index, for each frequency bin
The author has developed an FFT-based method for analysis that does
not require fiddle~, however, that method is not described in this paper.
Analysis/resynthesis models have historically been
oriented toward utilization of Fourier analysis of an audio
signal in order to deconstruct the spectra to its component
sine waves. Subsequently, the frequency and amplitude
information gleaned for each partial from the analysis is
distributed to a bank of oscillators for additive-based
resynthesis (Lippe, 1996). Once the spectral data is
acquired, a variety of modifications may be applied prior to
resynthesis (Settel and Lippe, 1994). However, alternate
methods of resynthesis may also be employed. This paper
describes an analysis/resynthesis technique in which Fourier
analysis is combined with FFT/IFFT-based spectral
attenuation. Also addressed are some of the intrinsic
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