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http://acervodigital.unesp.br/handle/11449/72054- Título:
- On the determination of epsilon during discriminative GMM training
- Universidade de São Paulo (USP)
- Universidade Estadual Paulista (UNESP)
- Shu-Te University
- Discriminative training of Gaussian Mixture Models (GMMs) for speech or speaker recognition purposes is usually based on the gradient descent method, in which the iteration step-size, ε, uses to be defined experimentally. In this letter, we derive an equation to adaptively determine ε, by showing that the second-order Newton-Raphson iterative method to find roots of equations is equivalent to the gradient descent algorithm. © 2010 IEEE.
- 1-Dez-2010
- Proceedings - 2010 IEEE International Symposium on Multimedia, ISM 2010, p. 362-364.
- 362-364
- Discriminative training of Gaussian Mixture Models (GMMs)
- Markov Models
- Speaker identification
- Speech recognition
- Discriminative training
- Gaussian mixture models
- Gradient descent algorithms
- Gradient Descent method
- Iteration step
- Newton-Raphson iterative method
- Second orders
- Speaker recognition
- Gaussian distribution
- Iterative methods
- Loudspeakers
- Markov processes
- http://dx.doi.org/10.1109/ISM.2010.66
- Acesso restrito
- outro
- http://repositorio.unesp.br/handle/11449/72054
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