Speaker emotional state classification by DPM models with annealed SMC samplers

Keyphrases

• Emotional State 100%
• Annealing 100%
• Dirichlet Process Mixture Model 100%
• State Classification 100%
• Sequential Monte Carlo Sampler 100%
• Speaker State 66%
• Training Data 33%
• Different Datasets 33%
• Classification Methods 33%
• Class Density 33%
• Emotional Speech 33%
• Bayesian Network 33%
• Posterior Density 33%
• Inference Algorithms 33%
• Number of Components 33%
• Comparable Accuracy 33%
• State-of-the-art Techniques 33%
• Sequential Monte Carlo Sampling 33%
• Minimum Distance Classifier 33%
• Content Representation 33%
• Unknown Number 33%
• Monitoring Time 33%
• Existing State 33%
• State Classes 33%

Computer Science

• Dirichlet Process 100%
• Emotional State 100%
• Training Data 33%
• Classification Method 33%
• Time Monitoring 33%
• Bayesian Networks 33%