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 Duration 14 hours (2 days)

Course Outline

Fundamentals of Audio AI

  • Defining Audio AI and its core capabilities
  • Distinguishing between voice, sound, and speech AI
  • Reviewing prominent tools and platforms in the market

Classifications of Audio AI Applications

  • Speech recognition and automated transcription
  • Voice assistants and conversational AI agents
  • Audio classification and event detection mechanisms

Industry-Specific Use Cases

  • Applications in customer service and contact centers
  • Use in media production, podcasting, and education
  • Roles in security, compliance, and law enforcement

Practical Interaction with Audio AI Tools (Demonstrations)

  • Performing live transcription using Whisper or Azure Speech
  • Enhancing basic audio quality with AI-driven noise reduction
  • Reviewing tools available for voice cloning and generation

Selecting the Appropriate Platform

  • Comparing Cloud APIs against open-source libraries
  • Assessing costs, accuracy, and scalability factors
  • Vendor analysis: Google, Microsoft, OpenAI, and ElevenLabs

Ethical and Legal Implications

  • Managing audio data privacy and user consent
  • Addressing the use of generated voices and deepfake technologies
  • Adhering to guidelines for safe and compliant deployment

Practical Lab: Implementing Audio AI Concepts

  • Hands-on exploration of tools for transcription, noise reduction, and classification
  • Small-group activities: selecting a business scenario and matching appropriate AI tools
  • Team discussions: identifying challenges, assumptions, and success metrics

Recap and Future Directions

Requirements

  • Basic familiarity with general AI or data-related concepts
  • Experience 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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