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RECoder

Organization : Art Center College of Design – Media Design Practice (Thesis project) Date : Jan. 2014 - Apr. 2014
Advisor : Elise Co(Aeolab)
Type : Design Fiction
Created with fabric, cardboard, elastic band, iPhone 4, Objective-C.






1. Project brief


In introducing new technologies, human-to-computer interaction design has borrowed familiar, human-to-human  communication methods to reduce cultural friction. At the same time, people have adopted human-to-computer interaction methods in their communications, creating a cultural and technological symbiosis. Natural-language interfaces — such as voice command systems — take part in this relationship, incorporating computers into traditional speaker-listener communication.

REcoder is fully working, fictional product in the near future, where we concede our verbal language to human to machine communication entirely, therefore people need a product that modified human speech into a form that machine can’t understand, but only human can. It is a wearable mask designed to explore the this extended realm of verbal communication where algorithmic listeners(computers with natural-language input) and human listeners coexist. REcoder processes its users’ speech and modifies it in real time according to an array of possible algorithmic filters as well as an alternative visual for the mouth, which addresses distinct characteristics between the two listeners. Its platform, muffling mask, alternative visuals, and algorithmic manipulations provide useful tools to explore synergistic relationship between technology and verbal language.






2. RECoder



REcoder’s mask part is designed to muffle the wearer’s voice completely to save him/her from getting into a trouble of accidentally activating any algorithmic listeners. Instead, REcoder live-translates what the wearer has said into special forms of speech that only human listeners can understand, through filters.

Each REcoder has a filter built in that live-translates the user’s speech. The filters are designed to exclude algorithmic listeners from human-to-human verbal communication by using the forms of speech that are traditionally considered to be inaccurate.







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