120 search results - page 12 / 24 » Maximum entropy models for speech confidence estimation |
TCBB
2010
13 years 6 months ago
2010
—Gene expression data usually contain a large number of genes, but a small number of samples. Feature selection for gene expression data aims at finding a set of genes that best...
ICASSP
2011
IEEE
2011
IEEE
Phoneme selective speech enhancement using the generalized parametric spectral subtraction estimator
12 years 11 months ago
In this study, the generalized parametric spectral subtraction estimator is employed in the context of a ROVER speech enhancement framework to develop a robust phoneme class selec...
ICASSP
2011
IEEE
12 years 11 months ago
2011
IEEE
We introduce Bayesian sensing hidden Markov models (BS-HMMs) to represent speech data based on a set of state-dependent basis vectors. By incorporating the prior density of sensin...
CVPR
2007
IEEE
14 years 10 months ago
2007
IEEE
We introduce novel discriminative learning algorithms for dynamical systems. Models such as Conditional Random Fields or Maximum Entropy Markov Models outperform the generative Hi...
ICML
2001
IEEE
14 years 8 months ago
2001
IEEE
We present conditional random fields, a framework for building probabilistic models to segment and label sequence data. Conditional random fields offer several advantages over hid...