In An Information Theory Based Compositional Model, Laurie Spiegel initially explains information theory, a mathematical theory optimizing signals for communication in noisy channels and addressing communication degradation in such environments. The author illustrates a drawback of applying information theory, noting that prolonged exposure may lead to increased listener boredom, as people can predict each note before hearing it.

Subsequently, the author delves into the use of noise in music to enhance its functionality. Introducing unpredictability through noise amplifies uncertainty in each note’s resolution, rendering it more musically interesting. This form of random corruption, distinct from random generation, involves replacing explicitly defined information with random data at random times to counteract redundancy and increase entropy in music. The author asserts that “music is self-referential and sensory rather than symbolic,” and defines music as “an art of sound in time expressing ideas and emotions in significant forms through the elements of rhythm, melody, harmony, and color.”

The concept of randomness has provided creators with limitless possibilities, and an increasing number of music programming software applications are incorporating this randomization utilizing a more diverse set of noises to enable individuals to create music, even without a background in music theory. Although unlike the author’s idea of random, my idea of “random” is more along the lines of “one can make simple music with many kinds of clips that already exist”.