Training strategies for deep latent models and applications to speech presence probability estimation

Keyphrases

• Training Strategy 100%
• Speech Presence Probability 100%
• Probability Estimation 100%
• Latent Model 100%
• Latent Variables 100%
• Neural Network 66%
• Neural Network Training 66%
• Expectation-maximization Algorithm 33%
• Speech Enhancement 33%
• Speech Processing 33%
• Gradient Method 33%
• Addressing Model 33%
• Latent Variable Models 33%
• Noise Reduction 33%
• Speech in Noise 33%
• Expectation Maximization 33%
• Backpropagation 33%
• Proposed Architecture 33%
• Speaker Separation 33%
• Number of Parameters 33%
• Mixture-of-experts 33%
• Speaker Diarization 33%
• Fully Connected Network 33%
• Neural Network Architecture 33%
• Back Propagation Algorithm 33%
• Expert Networks 33%

Engineering

• Probability Estimation 100%
• Latent Variable Model 100%
• Neural Network Training 100%
• Experimental Result 50%
• Tasks 50%
• Recursive 50%
• Speech Enhancement 50%
• Neural Network Architecture 50%
• Expectation Maximization Algorithm 50%
• Expert Network 50%
• Backpropagation Algorithm 50%
• Speech Processing 50%
• Maximization 50%
• Speakerdiarization 50%
• Backpropagation 50%
• Gradient-Based Algorithm 50%

Computer Science

• Neural Network 100%
• Neural Network Training 100%
• Latent Variable Model 100%
• Probability Estimation 100%
• Speech Processing 50%
• Speech Enhancement 50%
• Backpropagation 50%
• Speaker Diarization 50%
• Neural Network Architecture 50%
• Backpropagation Algorithm 50%
• Experimental Result 50%
• Connected Network 50%