Multimodal Affective Communication Analysis: Fusing Speech Emotion and Text Sentiment Using Machine Learning

Keyphrases

• Machine Learning 100%
• Speech Emotion 100%
• Communication Analysis 100%
• Affective Communication 100%
• Text Sentiment 100%
• Dynamic Bayesian 100%
• Bayesian Mixture Model 100%
• Emotions Sentiments 100%
• Speech-Text 100%
• Sentiment Analysis 75%
• Extended Dynamics 75%
• Speech Emotion Recognition 75%
• Two-layered 75%
• Emotional Understanding 50%
• Recognition Analysis 50%
• Multimodal Fusion 50%
• Logistic Regression 25%
• Support Vector Machine 25%
• Emotional State 25%
• Human Interaction 25%
• Superior Performance 25%
• Random Forest 25%
• Accuracy Rate 25%
• Emotional Speech 25%
• Ensemble Methods 25%
• Human-robot Interaction 25%
• Nonverbal Cues 25%
• Intercultural Communication 25%
• Individual Classifiers 25%
• Multilayer Perceptron 25%
• Deep Learning Model 25%
• Ensemble Model 25%
• Mental Health Screening 25%
• Classical Learning 25%
• Ensemble Classifier 25%
• GPT-2 25%
• Emotion Classification 25%
• Bidirectional Encoder Representations from Transformers 25%
• Diverse Features 25%
• Gaussian Naive Bayes 25%
• Method Fusion 25%
• Speech Conversion 25%
• Positive Contributions 25%
• Model Training 25%
• Model Evaluation 25%
• English Dataset 25%
• 1D Convolutional Neural Network (1D CNN) 25%

Computer Science

• Sentiment Analysis 100%
• Speech Emotion Recognition 100%
• Machine Learning 100%
• Learning System 100%
• Support Vector Machine 33%
• Superior Performance 33%
• Convolutional Neural Network 33%
• Bidirectional Encoder Representations From Transformers 33%
• Random Decision Forest 33%
• Individual Classifier 33%
• Individual Model 33%
• Deep Learning Model 33%
• Ensemble Method 33%
• Human Interaction 33%
• Logistic Regression 33%
• Multilayer Perceptron 33%
• Emotional State 33%
• Text To Speech 33%
• Individual Modality 33%
• ensemble classifier 33%
• Pre-Trained Model 33%
• Mental Disorder 33%