@inproceedings{4e7aa56d8fd247a4a4ad4044fae89a70,
title = "NMF with time-frequency activations to model non stationary audio events",
abstract = "Real world sounds often exhibit non-stationary spectral characteristics such as those produced by a harpsichord or a guitar. The classical Non-negative Matrix Factorization (NMF) needs a number of atoms to accurately decompose the spectrogram of such sounds. An extension of NMF is proposed hereafter which includes time-frequency activations based on ARMA modeling. This leads to an efficient single-atom decomposition for a single audio event. The new algorithm is tested on real audio data and shows promising results.",
keywords = "Music information retrieval, Non-negative matrix factorization, Unsupervised machine learning",
author = "Romain Hennequin and Roland Badeau and Bertrand David",
year = "2010",
month = jan,
day = "1",
doi = "10.1109/ICASSP.2010.5495733",
language = "English",
isbn = "9781424442966",
series = "ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "445--448",
booktitle = "2010 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2010 - Proceedings",
note = "2010 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2010 ; Conference date: 14-03-2010 Through 19-03-2010",
}