There seems to me no better way to begin this discussion than with an epistemological thought experiment (as is the case with most discussions). Consider what you heard in the “epiphone” to this essay, which is hiss from a digitization of recordings of Vachel Lindsay, originally made on aluminum records in 1931. It likely sounded like noise, and it is—to human auditory perception. But what if there is a pattern in this noise that is imperceptible to the human ear but recognizable to so-called machine listening? Consider the sample above from the Lindsay, alongside this sample of leading “noise” from digitizations of Harriet Monroe from the same series, alongside this one from the James Weldon Johnson recordings. I’ve been listening to several hours of audio from this series and have come to think that the noise from each of the recordings sounds similar, in the most impressionistic way possible.
It may seem odd that this commentary takes its name from a type of audio distortion, anathema to recording engineers who seek to capture crystalline representations of the human speaking voice. But just as all clear audio recordings must begin by having their levels set, so too must cutting-edge, experimental scholarship, which is what Clipping aims to present: inchoate working ideas on digital analyses of poetry audio. Rather than working to create a polished product off the record, as it were, we aim to publish brief working essays that the community can see and help to refine. As such, we hope to serve as a public platform and an incubator for experimental digital analyses of poetry.
In the coming months we will present a series of exciting posts by scholars working in the field of poetry audio. Ken Sherwood will explore visualizing poetry with special reference to audio versioning.
Through ARLO (Adaptive Recognition with Layered Optimization), enabled by the HiPSTAS (High Performance Sound Technologies for Access and Scholarship) project headquartered at the Information School of the University of Texas at Austin, I sought to visualize the later passages of Charles Bernstein's chanted/screamed list or counting poem, “1 to 100” (1969). Thanks to Chris Mustazza, Tanya Clement, David Tcheng, Tony Borries, Chris Martin, and others, I am finally learning how to use ARLO to some rudimentary effect. Every single PennSound recording is now available in a test space to which ARLO can be applied by researchers, including myself, associated with the project. We are just beginning. HiPSTAS has received two NEH grants to make all this possible, and PennSound is a founding archival partner.