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3. Noise Floor: Between Tinnitus and Raw Data
- University of Minnesota Press
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53 3 NOISE FLOOR: BETWEEN TINNITUS AND RAW DATA The claim is that one is opening music to all events, all irruptions, but one ends up reproducing a scrambling that prevents any event from happening. —Gilles Deleuze and Félix Guattari, A Thousand Plateaus Random corruption should not be confused with random generation. —Laurie Spiegel, “An Information Theory Based Compositional Model” what happens to music making under the conditions of networked computing? Just what is it that makes the bleeps and clicks of laptop music so different, so appealing? Our digital media culture is predicated on communication efficiencies to an extent that can obscure or veil the sources of noise, as faults, glitches, and bugs are too often relegated to the realm of the accidental. Yet glitch electronica puts precisely this raw material to creative use. Reduction of complexity is a highly successful strategy in the experimental laboratory, in system theory, and thus in many academic disciplines, but it points to a pivotal problem in digital transcoding of audiovisual “raw data,” regardless of whether the reduction at issue is an aesthetic strategy or a technical constraint. How much image can be omitted before an image is no longer an image? How much music can be compressed in lossy sampling before it ceases to be music? And conversely, how much information can be stored, processed, and 54 NOISE FLOOR transmitted without changing the frame of reference for visual arts, for music? Information theory is one approach to answering these questions ; the ultimate data compression is the entropy, H, and the ultimate transmission rate of communication is the channel capacity, C. However, this does not account at all for the success of glitch electronica in particular , nor indeed for the success of music in general. Tuning in to what is ordinarily filtered out, this chapter will investigate ways in which our signal-processing age has come to cope with raw data. In contemplating digital culture between a hermetically rule-bound realm of programmed necessity and efficient management of the totality of the possible, one can situate a realm of contingency: distortions in the strictest signal-to-noise ratio, glitches and accidents, or moments where what does not compute is condescendingly ascribed to error. It is from the “failure” of digital technology that this new work has emerged: glitches, bugs, application errors, system crashes, clipping, aliasing, distortion, quantization noise, and even the noise floor of computer sound cards are the raw materials composers seek to incorporate in their music.1 As our digital culture oscillates between the sovereign omnipotence of computing systems and the despairing agency panic of the user, digital tropes of perfect sound copies are abandoned in favor of errors, glitches become aestheticized, mistakes and accidents are recuperated for art under the conditions of signal processing. It is interesting to take a closer look at how this takes hold in music and sound art in an age of networked computing. Beyond the realm of traditional instruments, music has advanced rapidly by way of exploring the potential of storage, processing, and transmission of acoustic material. This soon led not only to the emulation of known sounds and patterns but to experiments with sonic expressions that had been either impossible or suppressed as noise and error. But this still begs the question how we distinguish between signal and noise in a musically meaningful way. “Noise does not have to be loud, but it has to be exclusive: excluding other sounds, creating in sound a bubble against [54.224.52.210] Project MUSE (2024-03-19 04:25 GMT) NOISE FLOOR 55 sounds.”2 Though arguably musical, an orchestra tuning up is generally considered to be noise, but the clapping of an audience, a form of white noise, is taken to be meaningful and, hence, signal: There is no absolute structural difference between noise and signal. They are of the same nature. The only difference we can logically establish between them hinges on the concept of intent on the part of the transmitter. A noise is a signal that the sender does not want to transmit.3 Of course, such a distinction would still privilege message over channel, intention over chance, and one may well object that musical practice has undermined such easy distinctions for centuries.4 However, the specific step that motivates the present argument is to see how the generative potential of computers is harnessed for electronic music, radically expanding the timbres and structures of creative sonic expression. Alva Noto’s work...