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ICPR
2004
IEEE
14 years 8 months ago
Bernoulli Mixture Models for Binary Images
Mixture modelling is a hot area in pattern recognition. Although most research in this area has focused on mixtures for continuous data, there are many pattern recognition tasks f...
Alfons Juan, Enrique Vidal
SPEECH
1998
171views more  SPEECH 1998»
13 years 7 months ago
Heteroscedastic discriminant analysis and reduced rank HMMs for improved speech recognition
We present the theory for heteroscedastic discriminant analysis (HDA), a model-based generalization of linear discriminant analysis (LDA) derived in the maximum-likelihood framewo...
Nagendra Kumar, Andreas G. Andreou
DAGM
2003
Springer
14 years 20 days ago
Improving Children's Speech Recognition by HMM Interpolation with an Adults' Speech Recognizer
In this paper we address the problem of building a good speech recognizer if there is only a small amount of training data available. The acoustic models can be improved by interpo...
Stefan Steidl, Georg Stemmer, Christian Hacker, El...
SSPR
2004
Springer
14 years 24 days ago
EM Initialisation for Bernoulli Mixture Learning
Mixture modelling is a hot area in pattern recognition. This paper focuses on the use of Bernoulli mixtures for binary data and, in particular, for binary images. More specificall...
Alfons Juan, José García-Herná...
KDD
2006
ACM
163views Data Mining» more  KDD 2006»
14 years 7 months ago
New EM derived from Kullback-Leibler divergence
We introduce a new EM framework in which it is possible not only to optimize the model parameters but also the number of model components. A key feature of our approach is that we...
Longin Jan Latecki, Marc Sobel, Rolf Lakämper