Published June 1, 2012 | Version v1
Conference paper Open

Towards Speeding Audio EQ Interface Building with Transfer Learning


Potential users of audio production software, such as parametric audio equalizers, may be discouraged by the complexity of the interface. A new approach creates a personalized on-screen slider that lets the user manipulate the audio in terms of a descriptive term (e.g. "warm"), without the user needing to learn or use the interface of an equalizer. This system learns mappings by presenting a sequence of sounds to the user and correlating the gain in each frequency band with the user's preference rating. The system speeds learning through transfer learning. Results on a study of 35 participants show how an effective, personalized audio manipulation tool can be automatically built after only three ratings from the user.



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