Identificador persistente para citar o vincular este elemento: http://hdl.handle.net/10553/43083
Título: A Chernoff-based approach to the estimation of transformation matrices for binary hypothesis testing
Autores/as: Lorenzo-García, F. D.
Ravelo-García, A. G. 
Navarro-Mesa, J. L. 
Martín-González, S. I. 
Quintana-Morales, P. J. 
Hernández-Pérez, E. 
Clasificación UNESCO: 3325 Tecnología de las telecomunicaciones
Palabras clave: Recognition
Fecha de publicación: 2006
Editor/a: Institute of Electrical and Electronics Engineers (IEEE) 
Publicación seriada: Proceedings of the ... IEEE International Conference on Acoustics, Speech, and Signal Processing 
Conferencia: 31st IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2006) 
Resumen: We present a new method for improving the classificacation score in the problem of binary hypothesis testing where the classes are modeled by a Gaussian mixture. We define a cost function which is based on the Chernoff distance and from it a transformation matrix is estimated that maximizes the separation between the classes. Once defined the cost function we derive an iterative method for which we give a simplified version where one mixture component per class is previously selected to participate in the estimation. The initialization of the method is studied and we give two possibilities for this. One is based on the Bhattacharyya distance and the other is based on the average divergence measure. The experiments are carried out over a database of speech with and without pathology and show that our approach represents an improvement in classification scores over other methods also based on matrix transformation.
URI: http://hdl.handle.net/10553/43083
ISBN: 1-­4244-­0469-­X/06
ISSN: 1520-6149
Fuente: Proceedings of the ... IEEE International Conference on Acoustics, Speech, and Signal Processing [ISSN 1520-6149], v. 5, p. 753-756, (2006)
Colección:Actas de congresos
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