Created by Benedict Hubener, Stephanie Lee and Kelvyn Marte at the CIID with the help from Andreas Refsgaard and Gene Kogan, ‘The Classyfier’ is a table that detects the beverages people consume around it and chooses music that fits the situation accordingly.

A built in microphone catches characteristic sounds and then compares these sounds to a catalogue of pre-trained examples. The Classyfier identifies it as belonging to one of three classes; hot beverages, wine or beer. Each class has its own playlist that one can navigate through by knocking on the table.

The idea behind this project was to build a smart object that uses machine learning and naturally occurring sounds as input to enhance the ambiance of different situations. The main tools used were Wekinator, Processing and the OFX collection.

Project Page | CIID