Nonlinear perceptual audio filtering using support vector machines

IEEE Workshop on Statistical Signal Processing Proceedings

Volumn , Issue , 2001, Pages 488-491

  Hill, Simon I ^a   Wolfe, Patrick J ^a   Rayner, Peter J W ^a  

^a UNIVERSITY OF CAMBRIDGE   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHMS; DISCRETE FOURIER TRANSFORMS; PROBABILITY DENSITY FUNCTION; VECTORS;

AUDIO FILTERS; SUPPORT VECTOR MACHINES (SVM);

SIGNAL FILTERING AND PREDICTION;

EID: 0035556208     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (14)

1. Towards a perceptually optimal spectral amplitude estimator for audio signal enhancement
2. Speech enhancement based on audible noise suppression
3. Single channel speech enhancement based on masking properties of the human auditory system
4. Speech enhancement using a minimum mean-square error short-time spectral amplitude estimator
5. Transform coding of audio signals using perceptual noise criteria
6. A tutorial on support vector regression
7. Fast training of support vector machines using sequential minimal optimization
8. Efficient SVM regression training with SMO
9. Probabilistic Kernel regression models
10. Support vector machines, reproducing Kernel Hilbert spaces and randomized GACV