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 Duration 14 hours

Course Outline

Introduction to Multimodal Interfaces

  • Defining multimodal interfaces
  • Advantages and complexities of multimodal engagement
  • Practical applications across diverse sectors

Multimodal AI in Human-Computer Interaction

  • Exploring human-centric AI design strategies
  • Core AI technologies underpinning multimodal interfaces
  • Cognitive and psychological aspects of human-AI partnership

Speech Recognition and Natural Language Processing (NLP)

  • Technologies for speech-to-text and text-to-speech conversion
  • Utilizing OpenAI's Whisper or Mozilla DeepSpeech
  • Enhancing the quality of AI-based voice interactions

Gesture Recognition and Motion Tracking

  • Analyzing hand tracking and bodily gestures
  • Integrating gesture controls into UI design
  • Practical application of open-source gesture recognition libraries

Eye Tracking and Gaze-Driven Interaction

  • Overview of eye-tracking technologies
  • Applications in accessibility and adaptive interface design
  • Creating gaze-based input mechanisms

Multimodal Fusion: Combining Input Methods

  • How AI synthesizes speech, gestures, and visual data
  • Constructing adaptive and personalized AI engagements
  • Best practices for creating cohesive multimodal experiences

Prototyping and Building Multimodal Interfaces

  • Designing intuitive, AI-driven interfaces
  • Prototyping multimodal interactions using Figma and AI tools
  • Developing practical applications with Python and AI frameworks

Testing and Assessing Multimodal Interfaces

  • Usability testing methods for multimodal AI systems
  • Quantifying user experience and satisfaction metrics
  • Optimizing and refining AI-driven interactions

Emerging Trends in Human-AI Collaboration

  • Progress in multimodal AI and deep learning
  • New developments in human-computer interaction
  • The future role of AI in shaping user experience

Recap and Future Directions

Requirements

  • Foundational knowledge of AI and machine learning concepts
  • Familiarity with UI/UX design best practices
  • Prior experience with programming, preferably in Python

Target Audience

  • UI/UX designers
  • Product managers
  • AI researchers

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