@inproceedings{683a60b45b1d4d6eb94ae49430968604,
title = "Music/Voice separation using the 2D fourier transform",
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.",
keywords = "2DFT, Audio source separation, auditory scene analysis, automatic karaoke, foreground/background separation, image processing, singing voice extraction",
author = "Prem Seetharaman and Fatemeh Pishdadian and Pardo, {Bryan A}",
note = "Funding Information: This work was supported by NSF Grant 1420971. Funding Information: ∗This work was supported by NSF Grant 1420971.; 2017 IEEE Workshop on Applications of Signal Processing to Audio and Acoustics, WASPAA 2017 ; Conference date: 15-10-2017 Through 18-10-2017",
year = "2017",
month = dec,
day = "7",
doi = "10.1109/WASPAA.2017.8169990",
language = "English (US)",
series = "IEEE Workshop on Applications of Signal Processing to Audio and Acoustics",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "36--40",
booktitle = "2017 IEEE Workshop on Applications of Signal Processing to Audio and Acoustics, WASPAA 2017",
address = "United States",
}