Algorithmic composition is the technique of using algorithms to create music.
Algorithms (or, at the very least, formal sets of rules) have been used to compose music for centuries; the procedures used to plot voice-leading in Western counterpoint, for example, can often be reduced to algorithmic determinacy. The term can be used to describe music-generating techniques that run without ongoing human intervention, for example through the introduction of chance procedures. However through live coding and other interactive interfaces, a fully human-centric approach to algorithmic composition is possible.
Some algorithms or data that have no immediate musical relevance are used by composers as creative inspiration for their music. Algorithms such as fractals, L-systems, statistical models, and even arbitrary data (e.g. census figures, GIS coordinates, or magnetic field measurements) have been used as source materials.
Compositional algorithms are usually classified by the specific programming techniques they use. The results of the process can then be divided into 1) music composed by computer and 2) music composed with the aid of computer. Music may be considered composed by computer when the algorithm is able to make choices of its own during the creation process.
Another way to sort compositional algorithms is to examine the results of their compositional processes. Algorithms can either 1) provide notational information (sheet music or MIDI) for other instruments or 2) provide an independent way of sound synthesis (playing the composition by itself). There are also algorithms creating both notational data and sound synthesis.
One way to categorize compositional algorithms is by their structure and the way of processing data, as seen in this model of six partly overlapping types:
translational models
mathematical models
knowledge-based systems
grammars
optimization approaches
evolutionary methods
systems which learn
hybrid systems
This is an approach to music synthesis that involves "translating" information from an existing non-musical medium into a new sound.
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This course will introduce students to the central topics in digital musicology and core theoretical approaches and methods. In the practical part, students will carry out a number of exercises.
A synthesizer (also spelled synthesiser) is an electronic musical instrument that generates audio signals. Synthesizers typically create sounds by generating waveforms through methods including subtractive synthesis, additive synthesis and frequency modulation synthesis. These sounds may be altered by components such as filters, which cut or boost frequencies; envelopes, which control articulation, or how notes begin and end; and low-frequency oscillators, which modulate parameters such as pitch, volume, or filter characteristics affecting timbre.
Aleatoric music (also aleatory music or chance music; from the Latin word alea, meaning "dice") is music in which some element of the composition is left to chance, and/or some primary element of a composed work's realization is left to the determination of its performer(s). The term is most often associated with procedures in which the chance element involves a relatively limited number of possibilities. The term became known to European composers through lectures by acoustician Werner Meyer-Eppler at the Darmstadt International Summer Courses for New Music in the beginning of the 1950s.
Generative music is a term popularized by Brian Eno to describe music that is ever-different and changing, and that is created by a system. In 1995 whilst working with SSEYO's Koan software (built by Tim Cole and Pete Cole who later evolved it to Noatikl then Wotja), Brian Eno used the term "generative music" to describe any music that is ever-different and changing, created by a system. The term has since gone on to be used to refer to a wide range of music, from entirely random music mixes created by multiple simultaneous CD playback, through to live rule-based computer composition.
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