Reduction of Non-stationary Noise using a Non-negative Latent Variable Decomposition |
Mikkel N. Schmidt, Jan Larsen
|
| Abstract | We present a method for suppression of non-stationary noise in single
channel recordings of speech. The method is based on nonnegative
sparse coding and relies on a voice activity detector. In
regions classified as non-speech, we learn an overcomplete basis for
the noise which is then used to estimate the speech and the noise
from the mixture. We compare the method to the classical approach
where the noise spectrum is estimated as the average of non-speech
frames. The proposed method significantly outperforms the classic
approach when the noise is highly non-stationary |
| Keywords | Non-stationary noise, spectral subtraction, |
| Type | Conference paper [With referee] |
| Conference | IEEE Machine Learning for Signal Processing Workshop |
| Year | 2008 |
| Publisher | Informatics and Mathematical Modelling, Technical University of Denmark, DTU |
| Address | Richard Petersens Plads, Building 321, DK-2800 Kgs. Lyngby |
| Electronic version(s) | [pdf] |
| BibTeX data | [bibtex] |
| IMM Group(s) | Intelligent Signal Processing |