Music/Voice separation using the 2D fourier transform

Prem Seetharaman, Fatemeh Pishdadian, Bryan A Pardo

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

4 Scopus citations

Abstract

Audio source separation is the act of isolating sound sources in an audio scene. One application of source separation is singing voice extraction. In this work, we present a novel approach for music/voice separation that uses the 2D Fourier Transform (2DFT). Our approach leverages how periodic patterns manifest in the 2D Fourier Transform and is connected to research in biological auditory systems as well as image processing. We find that our system is very simple to describe and implement and competitive with existing unsupervised source separation approaches that leverage similar assumptions.

Original languageEnglish (US)
Title of host publication2017 IEEE Workshop on Applications of Signal Processing to Audio and Acoustics, WASPAA 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages36-40
Number of pages5
ISBN (Electronic)9781538616321
DOIs
StatePublished - Dec 7 2017
Event2017 IEEE Workshop on Applications of Signal Processing to Audio and Acoustics, WASPAA 2017 - New Paltz, United States
Duration: Oct 15 2017Oct 18 2017

Publication series

NameIEEE Workshop on Applications of Signal Processing to Audio and Acoustics
Volume2017-October

Other

Other2017 IEEE Workshop on Applications of Signal Processing to Audio and Acoustics, WASPAA 2017
Country/TerritoryUnited States
CityNew Paltz
Period10/15/1710/18/17

Keywords

  • 2DFT
  • Audio source separation
  • auditory scene analysis
  • automatic karaoke
  • foreground/background separation
  • image processing
  • singing voice extraction

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Computer Science Applications

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