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 Duration 14 hours

Course Outline

Fundamentals of Audio AI

  • Defining Audio AI and its core functionalities
  • Distinguishing between voice, sound, and speech AI
  • Illustrations of widely used tools and platforms

Segments of Audio AI Applications

  • Speech recognition and automated transcription
  • Voice assistants and conversational interfaces
  • Audio classification and event identification

Industrial Applications and Use Cases

  • Customer support and contact center operations
  • Media production, podcasting, and educational sectors
  • Security, regulatory compliance, and law enforcement

Utilizing Audio AI Tools (Demonstrations)

  • Real-time transcription utilizing Whisper or Azure Speech
  • Fundamental audio improvement through AI-driven noise reduction
  • Overview of technologies for voice cloning and synthesis

Selecting an Appropriate Platform

  • Comparison of cloud APIs versus open-source libraries
  • Assessing expenses, precision, and scalability
  • Vendor analysis: Google, Microsoft, OpenAI, ElevenLabs

Ethical and Regulatory Factors

  • Privacy and consent regarding audio data
  • Implications of using synthesized voices and deepfakes
  • Best practices for secure and compliant implementation

Exploration Lab: Implementing Audio AI Concepts

  • Practical exploration of transcription, noise reduction, and classification utilities
  • Group-based activities: selecting a business scenario and aligning it with suitable AI tools
  • Collaborative discussions: identifying challenges, assumptions, and metrics for success

Conclusion and Future Directions

Requirements

  • A foundational grasp of general AI or data-related terminology
  • Basic familiarity with digital workflows or enterprise systems

Target Audience

  • Business leaders investigating AI-driven voice and audio solutions
  • Product managers and innovation teams assessing potential use cases
  • Government or corporate personnel engaged in digital transformation initiatives

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