Abstract
Deep Neural Networks (DNN) have become a popular approach
for speech enhancement, and singing voice separation.
DNNs are typically trained to estimate a timefrequency
mask using ground truth examples. In this submission,
we combine DNN estimation as a first step with
traditional refinement via F0 estimation, using the YINFFT
algorithm.
Bibtex
@inproceedings{Roma_2016d,
author = {Roma, G. and Grais, Emad and Simpson, A. J. R and Plumbley, M. D},
year = {2016},
month = aug,
title = {Singing Voice Separation using Deep Neural Networks and f0 Estimation},
booktitle = {MIREX 2016},
url = {http://www.music-ir.org/mirex/abstracts/2016/RSGP1.pdf},
keywords = {"maruss"}
}