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.
