Name
Abstract | ||
|---|---|---|
In this paper a method to remove noise in speech signals improving the quality from the perceptual point of view is presented. It combines spectral subtraction and two dimensional non-linear filtering techniques most usually employed for image processing. In particular, morphological operations like erosion and dilation are applied to a noisy speech spectrogram that has been previously enhanced by a conventional spectral subtraction procedure. Anisotropic structural elements on grayscale spectrograms have been found to provide a better perceptual quality than isotropic ones and reveal themselves as more appropriate for retaining the speech structure while removing background noise. Our procedure has been evaluated by using a number of perceptual quality estimation measures for several Signal-to-Noise Ratios on the Aurora database. |
Year | DOI | Venue |
|---|---|---|
2011 | 10.1007/978-3-642-25020-0_29 | NOLISP |
Keywords | Field | DocType |
speech structure,aurora database,perceptual point,speech enhancement,perceptual quality estimation measure,signal-to-noise ratios,morphological processing,background noise,noisy speech spectrogram,perceptual quality,spectral subtraction,conventional spectral subtraction procedure,spectrogram | Speech enhancement,Speech processing,Background noise,Dilation (morphology),Pattern recognition,Computer science,Spectrogram,Image processing,Filter (signal processing),Speech recognition,Artificial intelligence,Grayscale | Conference |
Volume | ISSN | Citations |
7015 | 0302-9743 | 3 |
PageRank | References | Authors |
0.41 | 4 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Joyner Cadore | 1 | 7 | 0.86 |
| j maciasguarasa | 2 | 92 | 19.30 |
| Carmen Peláez-moreno | 3 | 130 | 22.07 |