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INTERSPEECH
2010
13 years 2 months ago
HMM adaptation using linear spline interpolation with integrated spline parameter training for robust speech recognition
We recently proposed a method for HMM adaptation to noisy environments called Linear Spline Interpolation (LSI). LSI uses linear spline regression to model the relationship betwee...
Michael L. Seltzer, Alex Acero
ICASSP
2011
IEEE
12 years 11 months ago
Dirichlet Mixture Models of neural net posteriors for HMM-based speech recognition
In this paper, we present a novel technique for modeling the posterior probability estimates obtained from a neural network directly in the HMM framework using the Dirichlet Mixtu...
Balakrishnan Varadarajan, Garimella S. V. S. Sivar...
MLMI
2007
Springer
14 years 1 months ago
Posterior-Based Features and Distances in Template Matching for Speech Recognition
The use of large speech corpora in example-based approaches for speech recognition is mainly focused on increasing the number of examples. This strategy presents some difficulties ...
Guillermo Aradilla, Hervé Bourlard
ECCV
1994
Springer
13 years 11 months ago
Markov Random Field Models in Computer Vision
A variety of computer vision problems can be optimally posed as Bayesian labeling in which the solution of a problem is dened as the maximum a posteriori (MAP) probability estimate...
Stan Z. Li
MLMI
2005
Springer
14 years 26 days ago
Hierarchical Multi-stream Posterior Based Speech Recognition System
Abstract. In this paper, we present initial results towards boosting posterior based speech recognition systems by estimating more informative posteriors using multiple streams of ...
Hamed Ketabdar, Hervé Bourlard, Samy Bengio