Wind Noise Reduction Using Non-negative Sparse Coding |
Mikkel N, Schmidt, Jan Larsen, Fu-Tien Hsaio
|
| 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. |
| Keywords | NMF, Wind noise, single channel separation |
| Type | Misc [Presentation] |
| Journal/Book/Conference | IEEE International Workshop on Machine Learning for Signal Processing 2007 |
| Editors | K. Diamantaras, T. Adali, I. Pitas, J. Larsen, T. Papadimitriou, S. Douglas |
| Year | 2007 Month August |
| Publisher | ISP Group, Informatics and Mathematical Modelling, Technical University of Denmark |
| Address | Richard Petersens Plads, Building 321, DK-2800 Kgs. Lyngby, Denmark |
| Note | See 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 |