oyster

John Rose as Alan Lomax

 

oyster is a performance work in the form of a public lecture by renowned folk song collector Alan Lomax, whose 1960s Cantometrics project was intended to quantify and classify all folk musics from around the world—very much a precursor of contemporary machine learning and big data. I designed and directed the video component, in addition to writing the script and the score, so that these three elements could be tightly woven together. The work is a critical investigation of imperialism through big data and electronically mediated encounters between cultures.

Below is a short excerpt from the premiere at Roulette Intermedia in NYC. In the first section Lomax explains his basic principles of gathering folk-songs in the field, while the video shows something like a dance between Lomax and the song he’s after—personified by performer Saori Tsukada. In the second section, Lomax is using his Cantometrics system to break down the features of a particular region’s characteristic song:

 

The nine videos in the performance are the core of the work. In these, a vocal ensemble embodies Alan Lomax’s IBM 360 (performed by Christina Campanella, Michael Chinworth, John Rose, and Saori Tsukada). This is an experiment in Data Vocalization: I began with the data from Lomax’s Cantometrics study, which his team extracted by analyzing and rating 37 parameters of thousands of indigenous folk songs. The songs in oyster (which appear in the video behind Lomax himself) were all generated by mapping those ratings back into performed music. The inevitable gap between the original songs and our conversion of the data is meant to highlight the problematic assumptions underlying an imperialistic project, and to open up a critical space to think about biometrics, domination through databases, and electronically mediated encounters between cultures. Here are some brief excerpts from some of them:

 

For a detailed discussion of the project have a look at this article I recently wrote for PAJ: A Journal of Performance and Art.