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ICASSP
2009
IEEE
16 years 20 days ago
Modelling the prepausal lengthening effect for speech recognition: a dynamic Bayesian network approach
Speech has a property that the speech unit preceding a speech pause tends to lengthen. This work presents the use of a dynamic Bayesian network to model the prepausal lengthening ...
Ning Ma, Chris Bartels, Jeff A. Bilmes, Phil Green
ICCV
1999
IEEE
16 years 7 months ago
A Dynamic Bayesian Network Approach to Figure Tracking using Learned Dynamic Models
The human figure exhibits complex and rich dynamic behavior that is both nonlinear and time-varying. However, most work on tracking and synthesizing figure motion has employed eit...
Vladimir Pavlovic, James M. Rehg, Tat-Jen Cham, Ke...
HYBRID
2000
Springer
15 years 9 months ago
A Dynamic Bayesian Network Approach to Tracking Using Learned Switching Dynamic Models
Abstract. Switching linear dynamic systems (SLDS) attempt to describe a complex nonlinear dynamic system with a succession of linear models indexed by a switching variable. Unfortu...
Vladimir Pavlovic, James M. Rehg, Tat-Jen Cham
NN
1997
Springer
174views Neural Networks» more  NN 1997»
15 years 10 months ago
Learning Dynamic Bayesian Networks
Bayesian networks are directed acyclic graphs that represent dependencies between variables in a probabilistic model. Many time series models, including the hidden Markov models (H...
Zoubin Ghahramani
ICMCS
2006
IEEE
148views Multimedia» more  ICMCS 2006»
15 years 12 months ago
Acoustically-Driven Talking Face Synthesis using Dynamic Bayesian Networks
Dynamic Bayesian Networks (DBNs) have been widely studied in multi-modal speech recognition applications. Here, we introduce DBNs into an acoustically-driven talking face synthesi...
Jianxia Xue, Jonas Borgstrom, Jintao Jiang, Lynne ...