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http://hdl.handle.net/10553/46164
Title: | Support vector machines applied to the detection of voice disorders | Authors: | Godino-Llorente, Juan Ignacio Gomez-Vilda, Pedro Sáenz-Lechón, Nicolas Blanco-Velasco, Manuel Cruz-Roldán, Fernando Ferrer-Ballester, Miguel Angel |
UNESCO Clasification: | 3307 Tecnología electrónica | Keywords: | Mixture Speaker Models To-Noise Ratio Pathological Voices Speech Identification |
Issue Date: | 2005 | Journal: | Lecture Notes in Computer Science | Conference: | International Conference on Non-Linear Speech Processing International Conference on Non-Linear Speech Processing, NOLISP 2005 |
Abstract: | Support Vector Machines (SVMs) have become a popular tool for discriminative classification. An exciting area of recent application of SVMs is in speech processing. In this paper discriminatively trained SVMs have been introduced as a novel approach for the automatic detection of voice impairments. SVMs have a distinctly different modelling strategy in the detection of voice impairments problem, compared to other methods found in the literature (such a Gaussian Mixture or Hidden Markov Models): the SVM models the boundary between the classes instead of modelling the probability density of each class. In this paper it is shown that the scheme proposed fed with short-term cepstral and noise parameters can be applied for the detection of voice impairments with a good performance | URI: | http://hdl.handle.net/10553/46164 | ISBN: | 3540312579 9783540312574 |
ISSN: | 0302-9743 | Source: | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)[ISSN 0302-9743],v. 3817 LNAI, p. 219-230 |
Appears in Collections: | Actas de congresos |
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