Introduction
“The dynamic behavior of a mechanically produced sound is determined by the physical structure of the instrument that created it” (DePoli 223). The device of production is fundamental to the character of a sound. Nevertheless, most forms of synthesis function without regard to the physical attributes of the sound creation mechanism. Traditional synthesis algorithms take into account primarily the result of sound creation and pay less attention to the control devices that shaped the sound phenomena. More current algorithms, such as additive synthesis, have made use of Fourier analysis and synthesis with a great deal of success. Unfortunately, Fourier techniques are insufficient for the representation of non-pitched material. Physical model synthesis considers the mechanism of a real or imaginary instrument as the focus of the representation. Therefore, a physical model algorithm is capable of recreating aperiodic and transient sonorities produced by the vibrations of the sound creating structure. Scientists and engineers have been making use of physical models for quite some time. In 1971, Hiller and Ruiz were successful in using physical models to create musically useful sounds (Borin 30). Since that time, electronic musicians have explored the creation of sound through the implementation of instrument models. Currently available microprocessors have enabled many composers and performers to make use of physical models with a minimal investment.
Basics of Physical Model Synthesis
Building Blocks
Figure 1 displays a basic two-block scheme for a model. Here it is possible to see the two significant ³building blocks² necessary for physical model synthesis: the exciter and the resonator. Each of these blocks is defined using one of several different approaches (as discussed below).
Black-Box and White-Box Techniques
The resonator and exciter blocks are described in one of two ways: Black-Box or White-Box. These descriptions give a general idea of the complexity with which a model is constructed. Black box models (FIGURE 2a) are described only by an input and output relationship. The simplicity of the Black-Box model limits the choice of signals that can be involved in the description of the model and makes it difficult to choose the operative conditions of the model (Borin, 31-32). Thus, Black-Box techniques are not entirely useful for synthesis. White-Box (FIGURE 2b) models describe the entire mechanism of synthesis. Consequently, this synthesis strategy results in a flexible model that is quite difficult to apply and can quickly create a very large number of elements requiring simulation (Borin 32). The masses, springs, dampers, and conditional links described below are only present in a White-Box model; in a Black-Box model they are simply assigned a function.
Simple Objects
“A model must consider that which is manipulable, deformable, and animated by movements” (Florens 227). The primary objects in a sound-producing model are masses, springs, and dampers. Masses represent the material elements of the instrument, such as wood or brass, while springs and dampers represent linkage elements between the masses. These objects are obviously a substantial simplification to the actual sound creating mechanism, but much simplification is necessary to permit mathematical expressions in a single-dimension to be relatively accurate as well as manageable. Figure 3 shows a simple representation of a sound-producing object as a network.
The Fourth Object
Using the three elementary objects previously described, the number and variation of available groups or “blocks” is infinite. Nevertheless, these objects cannot fully represent a sound-creating mechanism because they offer no provision for collision with one another. Thus a fourth type of object, the conditional link, becomes necessary. Conditional links are links that are not permanent. They are composed of a spring and a damper and their function is determined by the material that connects them as well as musical circumstance. A conditional link may represent a bow striking a string, the hammers of a piano, or a variety of other temporary excitations.
Physical Model Techniques
Exciters
Before the synthesis of excitation can occur, it is necessary to determine the initial condition of the exciter. At the most fundamental level there exist only two types of initial conditions: those in which only one state of equilibrium exists (percussion), and those in which the exciter begins a new cycle of excitation from a variable equilibrium (bowed and wind instruments). Direct generation Modeling is a black-box technique for those instruments that are persistently excited. This technique may include any system that can generate an excitation signal. The most commonly used example is the table-lookup generator. Direct generation is usually incorporated into feed-forward coupling structures (see below). Memoryless Nonlinear Modeling is a black-box technique often used to model the exciter of wind instruments. This is because it generates an excitation signal that is derived from an “external” input signal that normally incorporates the excitation actions of the performer (FIGURE 4)(Borin 34). This model is also capable of using information that is coming from the resonator. Thus, the resonator’s reaction to an excitation influences the excitations that follow. Mechanical Modeling is a white-box technique where the exciter is described using springs, masses and dampers (FIGURE 5). Generally, excitations of this type are represented by a series of differential equations that govern the dynamic behavior of these elements (Borin 34). These models can be used to model almost any instrument.
Resonators
“The description of a resonator, without serious loss of generality, is reducible to that of a causal, linear, and time-varying dynamical system” (Borin 35). As with exciters, there are both black- and white-box techniques for modeling resonators. Both techniques can produce surprisingly musical results. Transfer-Function Modeling is a simple, black-box technique that ignores the physical structure of the resonator. The transfer-function model usually implements a transformation of pairs of dual variables, such as pressure and flow or velocity and force (Borin 35). Because this resonator is such a generic device, it is not the most musically useful resonator model. Mechanical Modeling of the resonator is very similar to mechanical modeling of the exciter. A series of differential equations are used to simulate the dynamic behavior of virtual masses, springs, and dampers. Waveguide Modeling is an efficient technique that is based on the analytic solution of the equation that describes the propagation of waves in a medium. For example, the waveguide model of the reed of a wind instrument requires only one multiply, two additions, and one table lookup per sample of synthesized sound (Smith 275). Because of the small number of simulations that it requires, this technique was the first to be incorporated into commercially available synthesizers.
Interaction
Just as there are several strategies for modeling exciters and resonators, there are numerous methods for controlling the interaction between the blocks. The Feed-forward technique (FIGURE 1) is the simplest structure by which exciter and resonator may be coupled. The transfer of information is unidirectional which prevents the excitation from being influenced by the resonance. “This structure lends itself particularly well for describing those interaction mechanisms in which the excitation imposes an initial condition on the resonator and then leaves it free to evolve on its own, or in which the excitation can be treated as a signal generator” (Borin 37). The Feedback technique (FIGURE 6) is a slight variation on feed-forward. The transfer of information is bi-directional and permits the modeling of most traditional instruments where a vibratory structure is influenced.
The most sophisticated interaction scheme, which is also the most computationally complex, is the Modular Interaction method. This model incorporates an interconnection block (FIGURE 7). The interconnection block acts as an interface; its main purpose is to separate the excitation from the resonator, so that they can be designed independently (Borin 38). Thus, the third blacks becomes the master of the information exchange between the exciter and the resonator.
Current Hardware and Software Developments
CORDIS/ANIMA
The CORDIS/ANIMA system is designed for the mechanical simulation of physical models. The CORDIS system originally ran on the LSI-11 type microcomputer from Digital Equipment Corporation. The system is capable of decomposing all aspects of the model into the most basic elements: masses, springs, and dampers. In 1985, the ANIMA update to CORDIS allowed modeling of two- and three-dimensional elements. This system was the first to fully incorporate conditional links.
Csound
Csound is a music programming language for IBM-compatible, Apple Macintosh, Silicon Graphics, as well as several other computers. It was written by Barry Vercoe at the MIT Media Lab. The programmer is required to give Csound an “Orchestra” file using an infinite number of instruments and instrument parameters, and a “Score” file that may be equally as complex. Csound then creates a soundfile containing the completed work.
A typical Csound “Orchestra” specification using the Karplus-Strong pluck algorithm:
; timbre: plucked string
; synthesis: Karplus-Strong algorithm(15)
; PLUCK with imeth = 1 (01)
; pluck-made series(f0) versus
; self-made random numbers(f77) (1)
sr = 44100
kr = 441
ksmps= 100
nchnls = 1
instr 1;
iamp = p4
ifq = p5 ; frequency
ibuf = 128 ; buffer size
if1 = 0 ; f0: PLUCK produces its own random numbers
imeth = 1 ; simple averaging
a1 pluck iamp, ifq, ibuf, if1, imeth
out a1
endin
instr 2;
iamp = p4
ifq = p5 ; frequency
ibuf = 128 ; buffer size
if1 = 77 ; f77 contains random numbers from a soundfile
imeth = 1 ; simple averaging
a1 pluck iamp, ifq, ibuf, if1, imeth
out a1
endin
A “Score” written for this particular “Orchestra”:
; GEN functions
; “Sflib/10_02_1.aiff” should exist
f77 0 1024 1 “Sflib/10_02_1.aiff” .2 0 0 ; start reading at .2 sec
; score
; iamp ifq
i1 0 1 8000 220
i1 2 . . 440
i2 4 1 8000 220
i2 6 . . 440
e
Many composers working with physical models currently use Csound. The power of the program to control even the smallest nuance of a soundfile, as well as the ability to import sampled sounds, and the convenience of recycling sophisticated “Orchestras” and “Scores”, make it a powerful physical modeler.
Conclusion
Physical modeling is a very powerful form of synthesis. Each of the techniques outlined above, whether they be recreations of general sound-production mechanisms, or an attempt at an exact reference to one specific instrument, provides a composer with an opportunity to expand his or her sonic “palette.” “It can be argued that often behind the use of physical models we find the quest for realism and naturalness, which is not always musically desirable. On the other hand we can notice that even with a physical model it is easy to obtain unnatural behaviors, by means of few variations of the parameters. Moreover, the acquired experience is useful in creating new sounds and new methods of signal organization” (DePoli 225). Physical models provide insight into the function of the instruments that composers have been working with for centuries. Perhaps gaining a better understanding of acoustic instruments, as well as developing systems that can accurately model them, will enable electronic musicians to create more dynamic, more deeply evolving timbres than previously thought possible.
References
Adrien, Jean-Marie. 1991. “The Missing Link: Modal Synthesis.” Representations of Musical Signals. Cambridge, Massachusetts: MIT Press, pp. 269-297.
Borin, Gianpaolo, et al. 1992. “Algorithms and Structures for Synthesis Using Physical Models.” Computer Music Journal 16(4):30-42.
DePoli, Giovanni. 1991. “Physical Model Representations of Musical Signals: Overview.” Representations of Musical Signals. Cambridge, Massachusetts: MIT Press, pp. 223-226.
Florens, Jean-Loup, and Cadoz, Claude. 1991. “The Physical Model: Modeling and Simulating the Instrumental Universe.” Representations of Musical Signals. Cambridge, Massachusetts: MIT Press, pp. 227-268.
Keefe, Douglas H. 1992. “Physical Modeling of Wind Instruments.” Computer Music Journal 16(4):57-73.
Smith, Julius. 1986. “Efficient Simulation of the Reed-Bore and Bow-String Mechanisms. “Proceedings of the 1986 International Computer Music Conference.” San Francisco: Computer Music Association.
Smith, Julius. 1992. “Physical Modeling Using Digital Waveguides.” Computer Music Journal 16(4):74-91.
Woodhouse, James. 1992. “Physical Modeling of Bowed Strings.” Computer Music Journal 16(4):43-56.