Wind Noise Reduction Using Non-negative Sparse Coding

Mikkel N, Schmidt, Jan Larsen, Fu-Tien Hsaio

AbstractWe 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.
KeywordsNMF, Wind noise, single channel separation
TypeMisc [Presentation]
Journal/Book/ConferenceIEEE International Workshop on Machine Learning for Signal Processing 2007
EditorsK. Diamantaras, T. Adali, I. Pitas, J. Larsen, T. Papadimitriou, S. Douglas
Year2007    Month August
PublisherISP Group, Informatics and Mathematical Modelling, Technical University of Denmark
AddressRichard Petersens Plads, Building 321, DK-2800 Kgs. Lyngby, Denmark
NoteSee also conference publication http://www.iimm.dtu.dk/pubdb/p.php?5258
Electronic version(s)[pdf]
BibTeX data [bibtex]
IMM Group(s)Intelligent Signal Processing


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