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.
|Title of host publication||Proceedings of New Interfaces for Musical Expression|
|State||Published - 2012|
|Event||NIME 2012 - Ann Arbor, MI|
Duration: May 1 2012 → …
|Period||5/1/12 → …|