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 language | English (US) |
---|---|
Title of host publication | 2017 IEEE Workshop on Applications of Signal Processing to Audio and Acoustics, WASPAA 2017 |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
Pages | 36-40 |
Number of pages | 5 |
ISBN (Electronic) | 9781538616321 |
DOIs | |
State | Published - Dec 7 2017 |
Event | 2017 IEEE Workshop on Applications of Signal Processing to Audio and Acoustics, WASPAA 2017 - New Paltz, United States Duration: Oct 15 2017 → Oct 18 2017 |
Publication series
Name | IEEE Workshop on Applications of Signal Processing to Audio and Acoustics |
---|---|
Volume | 2017-October |
Other
Other | 2017 IEEE Workshop on Applications of Signal Processing to Audio and Acoustics, WASPAA 2017 |
---|---|
Country/Territory | United States |
City | New Paltz |
Period | 10/15/17 → 10/18/17 |
Funding
This work was supported by NSF Grant 1420971. ∗This work was supported by NSF Grant 1420971.
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