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D&AD Annual 2020

See Sound
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  • DigitalCreative Use of Technology
  • Product DesignAssisted Living & Health
  • Digital DesignConnected Experiences
  • DigitalCreative Use of AI
  • Design TransformationDigital Transformation
  • Digital DesignNew Use of Technology
  • ImpactDesign/Brands
  • FutureProduct / Equality and Diversity

Year

  • 2020

Country

  • United States

Client

  • Wavio

Production Company

  • AREA 23, An FCB Health Network Company

Senior Producer

  • Elan Schoonmaker

Post Producer

  • Rob Gorrell

Account Director

  • Kristen Braun

Developer

  • Aaron Stack

Senior Integrated Producer

  • Jane Kim

Animator

  • Kenny Yee

Senior User Experience Architect

  • Peter Guirguis

Engagement Planner

  • Tyler Carroll

Product Designer

  • Katie Caputo

Design and Innovation Specialist

  • Munjen Ng

Chief Executive Officer

  • Greyson Watkins

Chief People Officer

  • Brandon Marin

Chief Operating Officer

  • Spencer Montan

Advertising agency; hardware design; production

  • AREA 23, an FCB Health Network Company

Brand; software design

  • Wavio

Industrial design

  • SIR Design LLC

Editorial; animation; post-production

  • Studio Rx, an FCB Health Network Company

Chief Creative Officer

  • Tim Hawkey

Group Creative Director

  • Joe Capanear
  • Chris Bernesby

Inventor and Associate Creative Director

  • Corinne Feight
  • Kristen Bell

Senior Art Director

  • Evan Schmidt

Photographer

  • Chris Hamilton

Advertising Agency

  • AREA 23, An FCB Health Network Company

Design Agency

  • SIR Design

Every person should be aware of what happens in their home. Yet for the millions of deaf and hard of hearing people worldwide, this still isn’t the case. There is no product available that can differentiate sounds, leaving consumers with nothing that can distinguish a microwave from a baby crying. Meet See Sound, the world’s first smart home hearing system. When a noise occurs, See Sound verifies it against a data library and translates it into a simple visual readout. Powered by two million YouTube video sound clips, this machine-learning model reports 75 sounds with industry-leading accuracy.