A method for rapid personalization of audio equalization parameters

Andrew T. Sabin, Bryan A Pardo

Research output: Chapter in Book/Report/Conference proceedingConference contribution

17 Scopus citations

Abstract

Potential users of audio production software, such as audio equalizers, may be discouraged by the complexity of the interface. We describe a system that simplifies the interface by quickly mapping an individual's preferred sound manipulation onto parameters for audio equalization. This system learns mappings by presenting a sequence of equalizer settings to the user and correlating the gain in each frequency band with the user's preference rating. Learning typically converges in 25 user ratings (under two minutes). The system then creates a simple on-screen slider that lets the user manipulate the audio in terms of the descriptive term, without need to learn or use the parameters of an equalizer. Results are reported on the speed and effectiveness of the system for a set of 19 users and a set of five descriptive terms.

Original languageEnglish (US)
Title of host publicationMM'09 - Proceedings of the 2009 ACM Multimedia Conference, with Co-located Workshops and Symposiums
Pages769-772
Number of pages4
DOIs
StatePublished - Dec 28 2009
Event17th ACM International Conference on Multimedia, MM'09, with Co-located Workshops and Symposiums - Beijing, China
Duration: Oct 19 2009Oct 24 2009

Publication series

NameMM'09 - Proceedings of the 2009 ACM Multimedia Conference, with Co-located Workshops and Symposiums

Other

Other17th ACM International Conference on Multimedia, MM'09, with Co-located Workshops and Symposiums
CountryChina
CityBeijing
Period10/19/0910/24/09

Keywords

  • Audio
  • Equalization
  • Interface
  • Music
  • Peronalization

ASJC Scopus subject areas

  • Computational Theory and Mathematics
  • Computer Science Applications
  • Computer Vision and Pattern Recognition
  • Software

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