Composer scores advance in high - tech tunes

43 By R. Colin Johnson paris — Just as IBM’s Deep Blue showed the world a computer can play chess as well as a human master, Eduardo Reck Miranda, a researcher for the Sony Computer Science Laboratory here, aims to demonstrate a computer program able to compose original music. So far, neural networks have succeeded in imitating distinct musical styles, but truly original compositions have remained elusive. Miranda is tackling that problem with an orchestra of virtual musicians— agents—who interact to compose truly original music. “From the viewpoint of a composer, I can hardly say that our agents are composing music at this stage,” Miranda acknowledged. Instead, he said, “The breakthrough in this work is the action of collective machine learning for generative music systems.” Rather than modeling specific musical styles or compositional processes, the new approach is a first step toward collective music-making with virtual musicians, each of which learns how to compose and play individually. The Brazilian-born Miranda composes chamber and electroacoustic pieces, compositions that have won prizes in the Americas, Asia and Europe. Today, at Sony, he specializes in artificial intelligence in music. In his latest book, Composing Music with Computers (Focal Press), Miranda summarizes his AI research, which began with cellular automata and evolved into an “adaptive games” strategy based on artificial-life models. “Perhaps one of the greatest achievements of artificial intelligence today lies in the construction of machines that can compose music of incredibly high quality,” he said. But AI’s achievement is restricted to mimicking the style of existing composers, either with a set of AI rules, or by learning a composer’s style with a neural network. In other words, computers can compose a new Bach cantata, but they will never compose anything novel, because their algorithms merely encapsulate a particular style of music. For a computer to create truly novel compositions, Miranda has turned to artificial life (AL) models—the new fodder for what he calls evolutionary musicology. The computer becomes endowed with an adaptive set of musiccomposition tools and processes. Under the control of an artificial life model the set displays “emergent” behaviors—that is, truly novel compositions. Miranda has explored this approach with cellular automata, genetic algorithm-like processes he summarized as “adaptive games.” He began his investigation with musical pieces composed using cellular automata, and created two computer programs to assist in the process—a software synthesizer called ChaoSynth and a generator of musical passages called Camus. Cellular automata are organized as a set of identical “cells” in a two-dimensional grid. Each has a set of rules to follow, but can only communicate with its nearest neighbors. The overall strategy is to begin with a simple set of rules affecting only local changes, but to evolve an overall organization that exhibits the emergence of new high-level structures—in this case, music. The process begins with a random distribution of cell states, then evolves a pattern through repeated application of each cell’s rule set in each time period. After an epoch of time periods, a pattern spontaneously emerges that is plain to see with the eye, as in the Game of Life, but is translated into a soundscape by Miranda’s ChaoSynth. ChaoSynth uses a granular synthesis method to translate the two-dimensional “Game of Life” pattern into a signal that can drive a speaker. By accumulating a sequence of short sound “grains”—typically 10 to 100 microseconds in length—many different cells can contribute to the final sound sample. Granular synthesis is often used to permit the pitch and duration of a sound to be adjusted independently, but the pitch and amplitude of Miranda’s sound grains were set by the rules being executed by each cell at any given time. “ChaoSynth is a successful system because it can synthesize a large amount of unusual sounds that are not normally found in