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 Duration 14 hours (2 days)

Course Outline

Introduction to Audio AI

  • Defining the core capabilities of Audio AI
  • Distinguishing between voice, sound, and speech AI
  • Overview 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

Industry-Specific Use Cases

  • Customer service and contact center operations
  • Media production, podcasting, and education
  • Security, compliance, and law enforcement

Working with Audio AI Tools (Demos)

  • Performing live transcription using Whisper or Azure Speech
  • Applying AI-based noise reduction for basic audio enhancement
  • Reviewing tools for voice cloning and generation

Selecting the Appropriate Platform

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

Ethical and Legal Considerations

  • Privacy and consent regarding audio data
  • Implications of using generated voices and deepfakes
  • Best practices for safe and compliant deployment

Exploration Lab: Applying Audio AI Concepts

  • Practical exploration of transcription, noise reduction, and classification tools
  • Small-group exercises: selecting a business case and mapping the appropriate AI tool
  • Team-based discussion: addressing challenges, assumptions, and success criteria

Summary and Next Steps

Requirements

  • Basic understanding of general AI or data-related terminology
  • 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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