Sonifying Hamlet uses data-mining techniques and algorithmic composition to read Shakespeare's Hamlet through sound. In so doing it attends to pre-semantic, textual data that is only visible when one steps back from reading for narrative and instead focuses on formal details that, being individually small, but collectively numerous, are more visible to computational sorting than they are to human eyes that have been trained to look for broad semantic content. This use of algorithmically generated sound to reconstruct textual data continues the western trend towards ubiquitous quantification, while also challenging that trend's underlying assumption that reality is reducible to fully discrete objects of study. That is, as nonlinguistic sound interacts with the other intonations of a place, it constructs a unique acoustic moment that obscures the distinction between individual datum, and between textual objects and the physical world. In this way, Sonifying Hamlet explores the physical and temporally constrained construction of an environment as a form of reading.

By simultaneously engaging with and resisting quantification trends in the digital humanities, Sonifying Hamlet attempts to inject ambiguity into a rising digital empiricism. In this way, it answers a call for such methods posed by digital humanists themselves for whom confrontation with the enigmatic is as potent a mode of knowing as scientific inquiry. Through its imbrication of the unnamable and the enumerated, Sonifying Hamlet attempts to support scholars by facilitating digital inquiry that is commensurate with the expansiveness of what is thinkable and expressible in human discourse.