@inproceedings{bf0a46a19b7a49f69088071241f1c1d8,
title = "Score informed audio source separation using a parametric model of non-negative spectrogram",
abstract = "In this paper we present a new technique for monaural source separation in musical mixtures, which uses the knowledge of the musical score. This information is used to initialize an algorithm which computes a parametric decomposition of the spectrogram based on non-negative matrix factorization (NMF). This algorithm provides time-frequency masks which are used to separate the sources with Wiener filtering.",
keywords = "audio source separation, machine learning, music information retrieval, non-negative matrix factorization",
author = "Romain Hennequin and Bertrand David and Roland Badeau",
year = "2011",
month = aug,
day = "18",
doi = "10.1109/ICASSP.2011.5946324",
language = "English",
isbn = "9781457705397",
series = "ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings",
pages = "45--48",
booktitle = "2011 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2011 - Proceedings",
note = "36th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2011 ; Conference date: 22-05-2011 Through 27-05-2011",
}