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Title Wind Noise Reduction in Single Channel Speech Signals
Author Andersen, Kristian Timm
Supervisor Larsen, Jan (Intelligent Signal Processing, Department of Informatics and Mathematical Modeling, Technical University of Denmark, DTU, DK-2800 Kgs. Lyngby, Denmark)
Institution Technical University of Denmark, DTU, DK-2800 Kgs. Lyngby, Denmark
Thesis level Master's thesis
Year 2008
Abstract In this thesis a number of wind noise reduction techniques have been reviewed, implemented and evaluated. The focus is on reducing wind noise from speech in single channel signals. More specifically a generalized version of a Spectral Subtraction method is implemented along with a Non-Stationary version that can estimate the noise even while speech is present. Also a Non-Negative Matrix Factorization method is implemented. The PESQ measure, different variations of the SNR and Noise Residual measure, and a subjective MUSHRA test is used to evaluate the performance of the methods. The overall conclusion is that the Non-Negative Matrix Factorization algorithm provides the best noise reduction of the investigated methods. This is based on both the perceptual and energy-based evaluation. An advantage of this method is that it does not need a Voice Activity Detector (VAD) and only assumes a-priori information about the wind noise. In fact, the method can be viewed solely as an advanced noise estimator. The downside of the algorithm is that it has a relatively high computational complexity. The Generalized Spectral Subtraction method is shown to improve the speech quality, when used together with the Non-Negative Matric Factorization.
Series IMM-M.Sc.-2008-18
Fulltext
Original PDF ep08_18_net.pdf (2.04 MB)
Admin Creation date: 2008-03-03    Update date: 2008-07-15    Source: dtu    ID: 211453    Original MXD