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GhostSynesthesia

Elementi d'informatica per il design, prof. Riboli, 2020/2021

Nine Inch Nails represents a hybrid difficult to define, an eclecticism of electronic sounds, heavy metal and industrial music characterized by an almost radical experimental spirit. In the 1990s the band produced numerous highly influential records, which brought them widespread popularity: many songs became hits, two albums won Grammy Awards, and the band sold over 20 million albums worldwide, including 10.5 millions sold in the United States alone. In 2004, Rolling Stone placed Nine Inch Nails in 94th place on their list of the 100 greatest rock artists of all time.

We could define the two new chapters of the "Ghosts" series, released during the pandemic of the last year, the instrumental and probably the most experimental soul of Nine Inch Nails, and it is precisely around this concept that our project took shape. Being the same two albums based on an immersive listening experience that at the choice of the authors practically does not need lyrics and words, we have designed a vinyl edition of the two albums, letting ourselves be inspired by the tracks treated in an attempt to offer the viewer a listening experience inspired by synaesthetic principles.

In the absence of literal texts, the task of transferring a message capable of communicating sensations, emotions and figures remains to the music, in its purest essence. Forcing the transmutation of meaning through the visualization we propose wants to provide a further apparatus of audiovisual assistance in which the sound transmutes into an image to invite new suggestions.

With this project we created two booklet - intended to be read as flipbooks to give the illusion of animation - with images instead of lyrics by using a sketch that creates a music responsive kaleidoscope.


The main code is based on Random Walker Kaleidoscope by Jacob Joaquin. https://www.openprocessing.org/sketch/135789

With the secondary code we created a tool for ourselves to apply a color filter to an entire batch of images and export them renamed accordigly. https://www.processing.org/reference/

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