Systems, methods, and apparatus for equalization preference learning

A system comprising:

• a processor configured to generate an interface, the interface receiving a first label for a first audio concept for a media object, the processor configured to:
• apply active learning to select a first example not yet rated by a first current user;
• collect a first user rating, by the first current user, of the first example compared to the first audio concept;
• apply transfer learning to combine the first user rating with ratings from prior users of examples not yet rated by the first current user to build a model of the first audio concept;
• and
• create a tool operable by the first user to generate examples close to and far from the first label to modify the media object.

A tangible computer readable medium comprising computer program code which, when executed by a processor, implements a method comprising:

• receiving a first label for a first audio concept for a media object;
• applying active learning to select a first example not yet rated by a first current user;
• collecting a first user rating, by the first current user, of the first example compared to the first audio concept;
• applying transfer learning to combine the first user rating with ratings from prior users of examples not yet rated by the first current user to build a model of the first audio concept;
• and
• creating a tool operable by the first user to generate examples close to and far from the first label to modify the media object.