Next Generation AI - Emotional Artificial Intelligence Based on Audio

Overview

Join us for an insightful exploration into the world of emotional artificial intelligence, where speech analysis offers groundbreaking insights into demographics, emotions, and health. Discover the potential of AI to revolutionize human-machine interactions across various industries, enhancing communication and understanding.

This event is a must-attend for anyone interested in the cutting-edge developments of AI technology and its practical applications in today's world.

Syllabus

• Introduction to Emotional AI
Overview of Emotional AI and its significance
History and evolution of emotional AI
Key differences between traditional AI and emotional AI
• Fundamentals of Speech Analysis
Basics of speech recognition technology
Phonetics and linguistics relevant to AI
Tools and software used in speech analysis
• Emotional Intelligence in AI
Understanding emotions and their representation in AI
Emotional recognition technologies and techniques
Case studies of emotional AI implementations
• Analyzing Demographics through Speech
Techniques for demographic prediction from audio data
Ethics and privacy concerns in demographic analysis
Applications in marketing, security, and UX design
• Emotion Detection and Analysis
Methods for detecting emotions in speech
Sentiment analysis tools and techniques
Applications in customer service and entertainment industries
• Health Insights from Audio Analysis
Identifying health markers in speech
Applications in telehealth and mental health diagnosis
Challenges and limitations in health-related AI analysis
• Technical Frameworks and Tools
Introduction to relevant AI frameworks and languages (e.g., Python, TensorFlow, PyTorch)
Practical exercises using tools for emotional and speech analysis
Building simple emotional AI models
• Ethical and Social Implications
Addressing biases in emotional AI systems
Discussing ethical considerations and responsible deployment
Impacts on societal norms and human interaction
• Future Directions and Innovations
Emerging trends in emotional AI and speech analysis
Potential future applications and industry impacts
Opportunities for research and development
• Capstone Project
Design and implement a basic emotional AI system
Analyze a specific application domain
Present findings and proposed solutions in a final presentation
• Course Wrap-up and Reflections
Summary of key learnings
Reflections and feedback session
Discussion on career paths in emotional AI and audio analysis

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Subjects

Conference Talks