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Starts 7 June 2025 18:59
Ends 7 June 2025
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Next Generation AI - Emotional Artificial Intelligence Based on Audio
Exploring emotional AI's ability to analyze speech for demographic, emotional, and health insights, revolutionizing human-machine interaction across industries.
MLCon | Machine Learning Conference
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MLCon | Machine Learning Conference
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41 minutes
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Overview
Exploring emotional AI's ability to analyze speech for demographic, emotional, and health insights, revolutionizing human-machine interaction across industries.
Syllabus
- Introduction to Emotional AI
- Fundamentals of Speech Analysis
- Emotional Intelligence in AI
- Analyzing Demographics through Speech
- Emotion Detection and Analysis
- Health Insights from Audio Analysis
- Technical Frameworks and Tools
- Ethical and Social Implications
- Future Directions and Innovations
- Capstone Project
- Course Wrap-up and Reflections
Overview of Emotional AI and its significance
History and evolution of emotional AI
Key differences between traditional AI and emotional AI
Basics of speech recognition technology
Phonetics and linguistics relevant to AI
Tools and software used in speech analysis
Understanding emotions and their representation in AI
Emotional recognition technologies and techniques
Case studies of emotional AI implementations
Techniques for demographic prediction from audio data
Ethics and privacy concerns in demographic analysis
Applications in marketing, security, and UX design
Methods for detecting emotions in speech
Sentiment analysis tools and techniques
Applications in customer service and entertainment industries
Identifying health markers in speech
Applications in telehealth and mental health diagnosis
Challenges and limitations in health-related AI analysis
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
Addressing biases in emotional AI systems
Discussing ethical considerations and responsible deployment
Impacts on societal norms and human interaction
Emerging trends in emotional AI and speech analysis
Potential future applications and industry impacts
Opportunities for research and development
Design and implement a basic emotional AI system
Analyze a specific application domain
Present findings and proposed solutions in a final presentation
Summary of key learnings
Reflections and feedback session
Discussion on career paths in emotional AI and audio analysis
Subjects
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