Last month sound artist Kate Carr wrote an article called Computer fatigue and the rise of the human which examines how and why some electronic musicians are turning away from the computer and digital recording/processing in favour of using analogue electronics and acoustic instruments. Apart from being an interesting article in itself, it caught my attention because it seems to relate to the complexity of sound in music. Complexity in music and visual art is a subject of deep interest for my work, both academic and creative, but it’s one that has been difficult to start writing about coherently. This post is an attempt to get the ball rolling. My initial aim was make a simple point about how the musicians’ strategies to counter computer fatigue can also be understood as a search for greater sonic complexity, but attempts to elaborate this point led to other avenues of thought. As such, the following ideas are still a bit sketchy.
Kate Carr’s article describes a trend amongst electronic musicians for increasing use of ‘real’ (as opposed to ‘virtual’) instruments. The “computer fatigue” in the title refers to a weariness or frustration with the characteristic sounds and techniques of digital audio. The problem with digital techniques, Carr notes, is that they undermine “spontaneity, accidents and the importance of live improvisation”. Musicians reveal a number of motivations for adopting a more lo-fi approach: a desire for greater authenticity, a nostalgia for retro technology, a search for ‘character’ or ‘soul’, and a need for manual control. Underlying all these motivations is a distaste for the precision, repeatability and consistency of digital audio. In contrast, more primitive technology offers a certain amount of variation in tone, timbre and timing. In addition, manual controls offer greater expressive capabilities and a more ‘human’ touch that also lead to greater variation in sound than digital methods. The appeal of the lo-fi is often expressed in terms of imperfection. For example, Zachary Corsa says that he prefers “imperfections and warmth to sterility and polished freeze”. Cameron Webb identifies the same thing in describing the difference compared with digital sound: “acoustic/analogue instrumentation … brings with it an element of imperfection”. The article concludes by citing the sensory philosophy of Michael Serres, using the metaphor of navigating the world of sound:
The closed off space of the computer offers an impoverished stage for such a voyage of self-discovery. Little wonder we have returned to the complexities, resonances, the physical strains and even failures that only an embodied experience of making and listening to sound can offer.
The complexity that Carr mentions in that final sentence is the idea I’d like to draw out here. Put simply, the imperfection of lo-fi approaches produces sounds that are more complex than their digital equivalent. Imperfection is a key characteristic of lo-fi sounds, and it is caused by the inherent instability of the instruments and the subtle variations of manual control. These deviations from the perfectly tuned and timed mean that no two sounds are exactly alike, therefore lo-fi instruments produce sounds that have greater variation than digital instruments, which are capable of producing exact copies of sounds. Greater variation means greater complexity. My doctoral research revealed that people understand visual complexity in terms of the level of detail and the variation of elements or patterns in a picture. Visual complexity is perceived to increase in proportion with the number of different colours and patterns, but decrease with repetition. Handmade images look more complex because of their small deviations from the straight and true, which makes them more interesting and more appealing. It seems plausible to suggest, therefore, that a similar effect occurs in music. In this sense, the condition of computer fatigue that has driven the move towards more lo-fi approaches can also be understood as a search for greater sonic complexity. (This doesn’t imply that this is very complex music; it just means that the sounds that musicians seek are rich and expressive, and it’s those properties that make them more complex.)
Computer fatigue may be explained by the fact that it is difficult to achieve natural or human variation using digital techniques. The alternatives to digital audio used by the musicians in Carr’s article offer easier ways to achieve musical variation. These include a range of technologies – manual (e.g. a glockenspiel), mechanical (pianoforte) and electronic (tape recorder, modular synthesizer). Each has their own characteristic imperfections, and each operates with different types of control mechanism that also contribute to the imperfections. To generate the same kind of pleasing variation in digital methods requires either painstaking adjustment of many details or the effort to introduce some randomness or non-linearity into the methods. Some musicians appear to have taken on this challenge, however, and are choosing to stick with the computer. The increasing sonic complexity of their music suggests that they too may suffer the symptom of computer fatigue, sharing the dissatisfaction with “impoverished” digital audio like the other musicians, but choosing instead to grasp the nettle and find new ways to generate greater sonic complexity using digital techniques. This is a theme that I’d like to expand upon.
The idea of a more natural variation or shaping of sound in digital music appeared in the recent ‘Ask Autechre Anything‘ thread on the WATMM forum (also available to view as a Google doc here). One question asked: “Given that you guys have been at the leading edge of sonic explorations for 20+ years have you developed any personal alternate theories and postulations about what music actually is?” Sean Booth’s response is a concise mathematical description:
yeah music = speech − text
at least roughly — i reckon it’s a kind of super-developed version of the pitch and intonation parts of speech (the aural bit that doesn’t contain textual info)
Autechre’s conception of music as “speech minus text” is supported by recent research in evolutionary psychology (e.g. the work of Diana Deutsch) which suggests that music has its origins in our faculty for producing and perceiving vocal sounds. Neurological studies suggest that speech and music are processed with similar mental circuits. The close ties between the two are also evidenced by education research that shows how participation in music can help to develop speaking and listening skills. This idea of music as ‘speech − text’ resonates because Autechre’s recent work seems to demonstrate a similar kind of naturally-formed sound. The music in Exai and L-Event in particular represent another step in the evolution of Autechre’s style, where the sounds seem to have a life of their own. These sounds are not quite organic (because they still sound synthetic, although less so than their previous work), but they are free from from the unappealing traits of digital audio. So, by being more complex sonically, Autechre represent an instance of musicians that share the condition of computer fatigue but who choose an alternative strategy to get away from the problems inherent in digital audio techniques. A similar aesthetic – perhaps a similar approach also – is perceivable in some of the output from Bill Kouligas’ PAN label, such as Traditional Music of Notional Species Vol. I by Rashad Becker and Dutch Tvashar Plumes by Lee Gamble:
Finally, I’d like to put forward the suggestion that these digital approaches to sonic complexity can be understood as an example of Manuel DeLanda’s idea of “topological music”, as described in his essay ‘The Virtual Breeding of Sound’ (PDF). The essay begins with a description of natural sounds – such as the song of a blackbird – that are formed via an evolutionary mechanism: “…these songs have becomes memes, patterns of behaviour transmitted through imitation and, as such, capable of having an evolution of their own.” The term “topological” refers to the type of morphological transformation driven by evolution – the ways in which biological forms evolve: growing, twisting, folding, extruding, wrinkling, but not cutting. DeLanda proposes topological transformations as a method of shaping sound and exploring musical possibilities. Techniques such as genetic algorithms can be used to generate new populations of sounds and select candidates for the next round of breeding. In this process, sounds evolve according to a set of fitness criteria, which constitute an abstract indication of desired properties rather than a specific and pre-determined design – a distinction made by DeLanda in terms of metric and non-metric (topological) geometries. In this way, these topological techniques offer a means to escape the predictability and uniformity of more primitive digital audio methods, thereby avoiding computer fatigue:
It is possible, although I do not know how to theorize this yet, that musicians will have to start thinking in terms of abstract musical structures where the key properties for a sound are not those of fixed duration or a fixed wavelength and the like, but rather are something else corresponding to what we may call “topological music”, something we cannot hear […] but which would define a rich search space, the final products of which would be audible. In turn, this implies representing within the computer something like the complex embryological processes, which map the genes (the genotype) into bodily traits (the phenotype), given that this complex mapping genotype-phenotype is where the conversion from topological to metric is achieved.
To support my argument that this other route away from computer fatigue may be characterized as topological music, I tried to find some information about these musicians’ techniques. Although lacking detail, it is clear that Autechre, Becker and Gamble still make use of the computer to shape sounds, develop rhythms and to structure music. The evolutionary aspect of topological music described by De Landa is hinted at with the inclusion of the word ‘species’ in the title of Rashad Becker’s album, as if the tracks were specimens of a new line of evolution. An interview with Becker supports this idea, where he discusses using software called The Brain that allows for sounds to be characterized and grouped according to shared ‘genetic’ characteristics between parent and offspring sounds. In accordance with Autechre’s conception of music as ‘speech minus text’, Becker also describes his music in terms of the characteristics of speech:
It’s the envelopes and the harmonic progressions that the sounds have that are all—like syllables, maybe. These are the progressions that I obviously, or naturally, or automatically look for, that resemble speech, breathing and performance, that represent a certain actual shape of a body.
Another description that I came across seems to capture this biological or non-digital aesthetic of topological music that I’m attempting to describe: “His sounds actually sound like things”, wrote Marc Masters in a review of Becker’s album. This description also matches how I feel listening to Autechre’s recent work. These strange new musical forms express a kind of internal mechanism that gives them a feeling of natural variation as well as a sense of coherence or family resemblance.
This topological music seems to share a similar rejection of sterile digital sounds with the musicians in Carr’s article. In both cases, the resulting music can be characterised as having hallmarks of complexity – greater variation of sonic materials and more complicated texture and structure. But the response to “computer fatigue” by the topological musicians contrasts with the work of those who choose the lo-fi approach as the solution. The critical difference is that the topological musics continue to use the computer and digital techniques. The topological techniques that DeLanda proposes, such as genetic algorithms, are forms of generative music composition. Philip Galanter’s definition of generative art provides a clear and concise way of understanding what generative methods involve:
Generative art refers to any art practice where the artist uses a system, such as a set of natural language rules, a computer program, a machine, or other procedural invention, which is set into motion with some degree of autonomy contributing to or resulting in a completed work of art. (2003, What Is Generative Art?)
The key element is that the artist gives some amount of creative control to the system. By this definition, strictly speaking, the strategies used by those musicians who have returned to lo-fi methods are also generative, though mainly at the lower level of sound structure rather than compositional structure. An instrument or method that produces sounds that vary in an unpredictable way constitutes a form of generative music system, because the musician is allowing the method to contribute some of its own characteristics. In effect, the system makes some of the creative decisions. In a digital system, these decisions would first have to be thought up and then programmed into the system. Because digital methods have to be instructed what to do, variation and surprise is more difficult to achieve. So, the return to lo-fi methods and the adoption of evolutionary digital techniques represent two forms of generative music that seek to avoid the condition of computer fatigue. They choose different routes to solve that problem, but in both cases a search for greater sonic complexity can be seen to motivate the creation of new music.
Nathan Thomas also wrote a response to Kate Carr’s article, Nature and the Nature-Like: A Response to the Computer-Fatigued, which questions the usefulness of authenticity or ‘reality’ as the dividing line between digital and analogue.