Facial Noise _demo

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Facial Noise uses facial expressions to generate and manipulate sounds. It explores the idea of the face as an interface - a remote control- that together with the sounds it generates turns into a tool of performance. The face, one of our strongest means of self-communication, is being analyzed by a software. The software, unobservable to the audience, is tracking the performer's facial features and movements, and uses the data in the process of the creation and mixing of the sounds.

The demo will be performed by the Butoh dancer Azumi Oe. In Butoh, the face is being used by the performer as a mask, freed from social constraints. Made out of muscles, the facial expressions that are being portrayed by the performer are empty from any subjective emotions. The audience is the one that creates the relationship between the expression and the performer that delivers it, creating an emotional bond between the two.

The Facial Noise interface explores human-computer interaction as a mean to generate musical expression. The experience will be presented in a 5-7 minutes of a live demo-performance, in any light-controlled space with sound system.

Facial Noise is a work in progress. The team is further researching and developing the software design, interaction, stage settings, sound design and choreography, which will increase the functionality of this tool as a musical note sheet.

Sound/Video tech flow:

Facial Noise is using FaceOSC and Max Jitter for face tracking. Kyle McDonald’s FaceOSC (based on the work of Jason Saragih) sends facial metrics via OSC using the ofxFaceTracker openFrameworks addon. The information, coming from Max and oF, is processed in Max MSP and Abelton Live, manipulating and creating new sound compositions. [Sound source: Macbook Pro, output via external sound card - Mbox2 pro (stereo 1/4 inch output)]. In this iteration we are using Mobiola installed on an iPhone, for a wireless video input and a monitor.

Thank you The HIVE NYC
thehivenyc.wix.com/thehive
and Juan Patino