Strong-sense class-dependent features for statistical recognition

Keyphrases

• Dependent Features 100%
• Class-dependent 100%
• Statistical Recognition 100%
• Recognition Accuracy 40%
• Conditional Probabilistic Model 40%
• Computational Requirements 20%
• Hidden Markov Model 20%
• Common Property 20%
• Design Approach 20%
• Storage Requirement 20%
• Classification Problem 20%
• Probabilistic Model 20%
• Input Pattern 20%
• Relative Entropy 20%
• Volume-preserving 20%
• Problem Recognition 20%
• Conditional Probability Density Function 20%
• Recognizer 20%
• Speech Recognition System 20%
• Statistical Classification 20%
• Phoneme Recognition 20%
• Contrast Feature 20%
• Heterogeneous Features 20%
• Feature Design 20%
• Linear Feature Transformation 20%

Engineering

• Recognition Accuracy 100%
• Objective Function 50%
• Probability Density Function 50%
• Linear Feature 50%
• Storage Requirement 50%
• Relative Entropy 50%
• Design Feature 50%
• Conditional Probability Density 50%
• Input Pattern 50%
• Classification Problem 50%
• Main Problem 50%
• Recognizer 50%
• Automatic Speech Recognition 50%
• Recognition Problem 50%

Computer Science

• Recognition Accuracy 100%
• Objective Function 50%
• Probability Density Function 50%
• Linear Feature 50%
• Storage Requirement 50%
• Classification Problem 50%
• Relative Entropy 50%
• Conditional Probability 50%
• Recognition Problem 50%
• Speech Recognition System 50%
• Recognizer 50%
• Statistical Classification 50%