Details

Project TitleEqualization Preference Learning Algorithm
Track Code2008-087
Short Description

An algorithm that rapidly determines a person's optimal sound quality

#software #soundsynthesis #datamining

Abstract

Northwestern researchers have developed an algorithm that rapidly determines a person's optimal sound quality, i.e. their desired equalization curves, without direct manipulation of a multitude of equalization controls. The process involves several steps. First, a reference sound is modified by a series of equalization curves. After each modification, the listener indicates how well the filtered sound exemplifies the target sound description (e.g. a "warm" sound). The algorithm generates a weighting function which modifies each channel based upon the user's response. This approach may be used to generate a filter for any particular electronic device, altering the frequency spectrum of a desired sound. The clear benefit is that this technology doesn't require the user to modify technical and complicated audio controls. In addition, some of the inventors also developed an additional ability to estimate the preferences of a particular user's sound quality based on previous user feedback. By comparing those ratings with prior users' preferences, the program can quickly tune to an audio quality that is ideal for the current user.

 
TagsSOFTWARE: sound synthesis, SOFTWARE: data mining
 
Posted DateNov 20, 2013 2:09 PM

Inventor(s)

Bryan Pardo

Andrew Sabin

Darren Gergle

David Little

Alexander Madjar

Applications

  • Phones
  • Audio devices (e.g. stereos, audio plug-ins, etc)
  • Hearing aids

Advantages

  • Intuitive user control to manipulate audio output

Publications

IP Status

Issued US Patent No. 8,565,908

Contact Information

Arjan Quist, PhD
Invention Manager
(p) 847.467.0305
(e) arjan.quist@northwestern.edu