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» Aggregation-based model reduction of a Hidden Markov Model
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INTERSPEECH
2010
14 years 10 months ago
Boosted mixture learning of Gaussian mixture HMMs for speech recognition
In this paper, we propose a novel boosted mixture learning (BML) framework for Gaussian mixture HMMs in speech recognition. BML is an incremental method to learn mixture models fo...
Jun Du, Yu Hu, Hui Jiang
CVPR
2007
IEEE
16 years 6 months ago
Real-time Gesture Recognition with Minimal Training Requirements and On-line Learning
In this paper, we introduce the semantic network model (SNM), a generalization of the hidden Markov model (HMM) that uses factorization of state transition probabilities to reduce...
Stjepan Rajko, Gang Qian, Todd Ingalls, Jodi James
ICPR
2010
IEEE
15 years 1 months ago
Audio-Visual Classification and Fusion of Spontaneous Affective Data in Likelihood Space
This paper focuses on audio-visual (using facial expression, shoulder and audio cues) classification of spontaneous affect, utilising generative models for classification (i) in t...
Mihalis A. Nicolaou, Hatice Gunes, Maja Pantic
ENTCS
2006
134views more  ENTCS 2006»
15 years 4 months ago
Partial Order Reduction for Probabilistic Branching Time
In the past, partial order reduction has been used successfully to combat the state explosion problem in the context of model checking for non-probabilistic systems. For both line...
Christel Baier, Pedro R. D'Argenio, Marcus Grö...
ICML
2007
IEEE
16 years 4 months ago
Multi-task learning for sequential data via iHMMs and the nested Dirichlet process
A new hierarchical nonparametric Bayesian model is proposed for the problem of multitask learning (MTL) with sequential data. Sequential data are typically modeled with a hidden M...
Kai Ni, Lawrence Carin, David B. Dunson