Wind Noise Reduction using Non-negative Sparse Coding |
Mikkel N. Schmidt, Jan Larsen, Fu-Tien Hsiao
|
| 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. |
| Type | Conference paper [With referee] |
| Conference | IEEE International Workshop on Machine Learning for Signal Processing |
| Editors | |
| Year | 2007 Month August pp. 431-436 |
| Publisher | Informatics and Mathematical Modelling, Technical University of Denmark, DTU |
| Address | Richard Petersens Plads, Building 321, DK-2800 Kgs. Lyngby |
| ISBN / ISSN | ISBN: 1-4244-1566-7 |
| Note | This publication includes a supplementary windnoise database [zip file] used in the publication |
| Electronic version(s) | [pdf] [zip] |
| BibTeX data | [bibtex] |
| IMM Group(s) | Intelligent Signal Processing |