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 Duration 14 hours

Course Outline

Introduction to Multimodal Interfaces

  • Defining multimodal interfaces
  • Advantages and obstacles in multimodal interactions
  • Practical applications across various sectors

Multimodal AI and Human-Computer Interaction

  • Principles of human-centric AI design
  • Core AI technologies underpinning multimodal interfaces
  • Psychological and cognitive aspects of human-AI partnership

Speech Recognition and Natural Language Processing (NLP)

  • Technologies for speech-to-text and text-to-speech
  • Leveraging OpenAI's Whisper or Mozilla DeepSpeech
  • Enhancing voice-based AI interactions

Gesture Recognition and Motion Tracking

  • Insights into hand tracking and body movement analysis
  • Integrating gesture control into UI design
  • Practical application of open-source gesture recognition libraries

Eye Tracking and Gaze-Based Interaction

  • Overview of eye-tracking technology
  • Applications in accessibility and adaptive UIs
  • Creating input systems based on gaze direction

Multimodal Fusion: Combining Multiple Input Methods

  • How AI synthesizes speech, gestures, and visual data
  • Building adaptive, personalized AI interactions
  • Best practices for cohesive multimodal experiences

Prototyping and Implementation of Multimodal Interfaces

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

Testing and Evaluation of Multimodal Interfaces

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

Future Directions in Human-AI Collaboration

  • Advances in multimodal AI and deep learning
  • New trends in human-computer interaction
  • The role of AI in shaping future user experiences

Summary and Recommended Next Steps

Requirements

  • Foundational knowledge of AI and machine learning principles
  • Working familiarity with UI/UX design standards
  • Preliminary programming experience (Python is recommended)

Target Audience

  • UI/UX designers
  • Product managers
  • AI researchers

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