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 Duration 14 hours

Course Outline

Introduction to Audio AI

  • Defining Audio AI and outlining its core capabilities
  • Differentiating between voice, sound, and speech AI
  • Reviewing examples of popular tools and platforms

Categories of Audio AI Applications

  • Speech recognition and automatic transcription
  • Voice assistants and conversational agents
  • Audio classification and event detection

Use Cases Across Industries

  • Customer service and contact center operations
  • Media, podcasting, and educational sectors
  • Security, compliance, and law enforcement contexts

Working with Audio AI Tools (Demonstrations)

  • Performing live transcription using Whisper or Azure Speech
  • Applying basic audio enhancement through AI noise reduction
  • Overview of tools for voice cloning and generation

Selecting the Appropriate Platform

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

Ethical and Legal Considerations

  • Audio data privacy and consent management
  • Implications of using generated voices and deepfakes
  • Guidelines for ensuring safe and compliant deployment

Exploration Lab: Applying Audio AI Concepts

  • Hands-on exploration of transcription, noise reduction, and classification tools
  • Small-group exercises: Selecting a business case and mapping appropriate AI tool fit
  • Team-based discussions: Addressing challenges, assumptions, and success criteria

Summary and Next Steps

Requirements

  • A foundational understanding of general AI or data-related terminology
  • Familiarity with digital workflows or enterprise systems

Target Audience

  • Business leaders exploring AI-driven voice and audio solutions
  • Product managers and innovation teams evaluating potential use cases
  • Government or corporate staff involved in digital transformation initiatives

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