The Yassifier

Mirror mirror on the wall, why don't I recognise myself at all?

MaxMSP

Electret microphone

Online data

Spark AR

prompt

A humanised algorithm

Coaches & collaborators

institute

Design Academy Eindhoven

Poreless skin, pillow lips, a tiny nose and high cheekbones. While apps like Faceapp allow us to edit our faces however we want, they also set an impossible beauty standard, where we end up competing with a pretend version of ourselves. The Yassifier (from “yassifying” - applying several beauty filters until one becomes unrecognisable) is a humorous response to this real issue. The heavy face filter creates a reaction in the user - depending on their facial expression, their voice gets further distorted, creating an even bigger divide between our real and digital selves.

process & design

Project images

No items found.

the tech

How does it work?

The Yassifier functions with 2 different cameras: the IPad’s frontal camera, to enable the face filter made in Spark AR which is displayed on the screen live, and a webcam installed on top that is connected to a laptop. In the laptop, a facial expression recognition algorithm made in JavaScript is running and identifying 7 different emotions, which are then turned into numerical data. Then, in MAX MSP, each emotions’ data is fed to a respective RNBO audio effect that alters the sound live. For example, when smiling and talking simultaneously, the sound emitted by MAX will be the user’s voice but in a much higher pitch.

Open source code

Click here to grab this project's code

MaxMSP

Visual programming language for music and multimedia

Electret microphone

Record or detect audio gain (volume) changes

Online data

Captures data in real time from web APIs

Spark AR

AR design tool