@CONFERENCE\{IMM2007-05258,
    author       = "M. N. Schmidt and J. Larsen and F. Hsiao",
    title        = "Wind Noise Reduction using Non-negative Sparse Coding",
    year         = "2007",
    month        = "aug",
    pages        = "431-436",
    booktitle    = "{IEEE} International Workshop on Machine Learning for Signal Processing",
    volume       = "",
    series       = "",
    editor       = "Konstantinos Diamantaras, Tülay Adali, Ioannis Pitas, Jan Larsen, Theophilos Papadimitriou, Scott Douglas",
    publisher    = "Informatics and Mathematical Modelling, Technical University of Denmark, {DTU}",
    organization = "",
    address      = "Richard Petersens Plads, Building 321, {DK-}2800 Kgs. Lyngby",
    note         = "This publication includes a supplementary windnoise database [zip file] used in the publication",
    url          = "http://www2.compute.dtu.dk/pubdb/pubs/5258-full.html",
    abstract     = "We introduce a new speaker independent method for reducing
wind noise in single-channel recordings of noisy speech. The
method is based on non-negative sparse coding and relies on a
wind noise dictionary which is estimated from an isolated noise
recording. We estimate the parameters of the model and discuss
their sensitivity. We then compare the algorithm with the classical
spectral subtraction method and the Qualcomm{-ICSI-OGI} 
noise reduction method. We optimize the sound quality in terms of
signal-to-noise ratio and provide results on a noisy speech recognition
task.",
    isbn_issn    = "ISBN: {1-}4244-1566-7"
}