Sounds, Signals, and Glitches: A Monday Morning Commute

Having appreciated our reading from Digital Sound Studies, I wanted to first vouch for the keen way in which the book’s editors introduce readers to this rising field of multimodal inquiry, often striking a balance between the ethical and intellectual currents of sound-centric inquiry. As difficult as it is to initiate readers to new types of criticism, the act of presenting a radical new mode of scholarship altogether is truly another beast, not least because the academy is known for clinging to its standards in communication and praxis. Lingold, Mueller, and Trettien problematize this matter when discussing the disciplinary origins of the digital humanities, in particular, writing that the “answer lies in the text-centricity of the field, a bias that is baked into its institutional history,” borne out by text-based journals like Literary and Linguistic Computing and social media platforms like Twitter (10). Given that text-centricity permeates academic knowledge production and thus shapes the disciplinary ethos of DH, I suspect the field cannot afford to overlook multimodal initiatives without continuing to suffer from the tacit biases of text-centric thinking. With that said, I’m immediately inclined to point out the elephant in the room by noting that the text-centered format of my blogpost is an irony not lost on me. It is actually in light of acknowledging this irony that I’ve decided to use this post as a space to not only think about but also try out some of the critical methods outline in the introduction to Digital Sound Studies.

Accordingly, one train of thought and practice that I’m interested in pursuing here relates to “what counts as “sound” or “signal” and what gets dismissed as “noise”… across listening practices,” focusing perhaps on how certain sounds inscribe meaning into our unselfconscious experience of digital tools and social spaces (5). Broadly speaking, the myriad sounds of digital technology run the gamut in how they signify meaning to users. For instance, on one end of the digital spectrum, we have the bubbly sound effect that Facebook emits when aggregating user feeds, all but patching its simulation of our “real-time” social community. Meanwhile, on the other end, we have the IBM beep codes of a power-on self-test (POST), configured so that computer systems will self-assess for internal hardware failures and communicate their results to users (who in return seldom think twice). Fascinating as cybernetics can be, I’ve found myself even more drawn to analyzing how this hypercritical approach to digital sounds can shed light our experience of the relation between sound and noise in daily routines.

Take, for example, my daily commute. Inauspiciously swiping my MetroCard yesterday, I came across the dreaded beeping sound of a turnstile failing to register my magnetic strip, joyously accompanied by that monochromatic error message which politely requests tepid MTA riders to Please swipe again or Please swipe again at this turnstile. As residents of NYC, it’s a sound effect we know too well — and yet I decided to record and embed it below, along with the next 90 or so seconds of this Monday morning commute to Manhattan.

https://soundcloud.com/zmuhlbauer1/mta-voiceover

The recording then teeters about for a moment until the rattling hum of the train grows more and more apparent. After grinding to a stop, its doors hiss open, the MTA voiceover plays, and I enter the subway car to find the next available seat.

https://soundcloud.com/zmuhlbauer1/from-hewes-to-marcy

Though straightforward at a glance, many of these sounds work not unlike commas in a CSV file, similarly but more loosely enacting delimiters for one of the key duties of the NYC subway system: to safely prompt passengers onto and out of subway cars. Together with verbally recorded cues, in other words, MTA voiceovers appear to serve as markers of not only spatial but also temporal cues. By way of example, consider the following series of sound signals: the turnstile’s beep effect marks a transition into the self-enclosed space of the station; the M-train arrives and emits its door-opening voiceover, which at once marks the line progression and the onset of when riders may enter the train, framed off by the (in)famous MTA line, Stand clear of the closing of the closing doors please. Exiting the train, I was struck by the fact that I had only twice acknowledged the sound of the voiceover (getting on at Hewes Street and getting off at Herald Square station), despite there being several other stops between. It follows that these sound effects contain locally assigned meaning, produced in accordance with the intentionality or focus of the subject — or, in this case, the individual passenger. Herein lies the difference between sound and noise. We inscribe symbolic value to sound on the basis of perceived relevance, of functional utility, but have no immediate use for noise, which in turn blends into white noise, accounting for why sound is specific and noise nonspecific. Put differently, we choose to hear certain sounds because they are unsurprisingly meaningful to us and our purposes — e.g. hearing your name in a crowd — while we neglect the indiscrete stuff of noise because it is peripheral, useless. While sound resembles our impressions of order, noise veers closer to our impressions of disorder.

Exiting the train, I was struck by the fact that I had only twice acknowledged the sound of the voiceover (getting on at Hewes Street and getting off at Herald Square station), despite there being several other stops between. It follows that these sound effects contain locally assigned meaning, produced in accordance with the intentionality or focus of the subject — or, in this case, the individual passenger. Herein lies the difference between sound and noise. We inscribe symbolic value to sound on the basis of perceived relevance, of functional utility, but have no immediate use for noise, which in turn blends into white noise, accounting for why sound is specific and noise nonspecific. Put differently, we choose to hear certain sounds because they are unsurprisingly meaningful to us and our purposes — e.g. hearing your name in a crowd — while we neglect the indiscrete stuff of noise because it is peripheral, useless. While sound resembles our impressions of order, noise veers closer to our impressions of disorder.

To further ground my thoughts in the context of DH and digital sound studies, also consider the interrogative voice at the end of the recording from above. As some might guess, once the MTA voiceover begins to fade out, the recording very clearly catches a homeless man’s appeal for food from passengers on the train. Intending initially to catch clearly recorded sounds of the MTA subway system, my knee-jerk reaction here was to either edit the file (the one embedded above), or to simply cut my losses and rerecord when returning home later that day. Since it felt heavy-handed to run through the whole process again and convolute the integrity of my data-collection process, I elected to edit the video at first. But it was only shortly after that I started to think more honestly about why I wanted to record my commute in the first place. In turn, I determined that this interruption did not misrepresent my commute so much as it merely deviated from what I anticipated — and thus intended — to record out of my commute, if only to realize the extent to which these these interrogative sounds were crucially embedded in my experience of the ride and its sounds. No amount of edit will change that fact, so here below I’ve included the full recording:

https://soundcloud.com/zmuhlbauer1/from-hewes-to-marcy-1

Needless to say, sudden appeals for food or money on these tight subway cars can have an awkward or troubling effect on passengers, who in return may go quiet, look down or away, resort to headphones, or read absently until it’s over. As is common, the man in this recording recognizes this particular social reality, evident in how he prefaces his appeal by saying “I’m really sorry to disturb you.” Similar to the many for whom this experience is semi-normalized, I’m inclined to likewise ignore these interruptions for the same reason that I rushed to edit my recording in pursuit of an uninterrupted soundbite — that is, because I’m regulated to perceive these appeals as just another unavoidable case of NYC noise, brushed off as an uncomfortable glitch in the matrix of urban American society.

Like “the cats batting at Eugene Smith’s microphone” and refocusing listeners to “the technology itself,” it’s clear that such disturbances enable us to reinspect our use of digital technology, often in ways that reveal the naturalized conditions of daily social life and more (3). I cannot help but think back to the part of Race After Technology when Ruha Benjamin speaks to the illuminating potential of digging deeper into glitches; and how these anomalies can act as key resources in the fight to reveal hidden insights about the invisible infrastructures of modern technology. With that in mind, I’ll end with an excerpt of hers, one whose words to me ring a little louder today than they did in days prior.

Glitches are generally considered a fleeting interruption of an otherwise benign system, not an enduring and constitutive feature of social life. But what if we understand glitches to be a slippery place (with reference to the possible Yiddish origin of the word) between fleeting and durable, micro-interactions and macro-structures, individual hate and institutional indifference? Perhaps in that case glitches are not spurious, but rather a kind of signal of how the system operates. Not an aberration but a form of evidence, illuminating underlying flaws in a corrupted system (80).