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Course Outline

Foundations of Audio AI

  • Defining Audio AI and its core capabilities
  • Distinctions between voice, sound, and speech AI
  • Examples of prominent tools and platforms

Categories of Audio AI Applications

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

Cross-Industry Use Cases

  • Customer service and contact centers
  • Media, podcasting, and educational sectors
  • Security, compliance, and law enforcement

Working with Audio AI Tools (Demos)

  • Live transcription using Whisper or Azure Speech
  • Fundamental audio enhancement via AI noise reduction
  • Overview of tools for voice cloning and generation

Selecting the Right Platform

  • Cloud APIs versus open-source libraries
  • Evaluating costs, accuracy, and scalability
  • Vendor comparison: Google, Microsoft, OpenAI, ElevenLabs

Ethical and Legal Considerations

  • Audio data privacy and consent
  • Utilization of generated voices and deepfakes
  • Guidelines for secure 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 aligning AI tool fit
  • Team-based discussion: challenges, assumptions, and success criteria

Summary and Next Steps

Requirements

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

Target Audience

  • Business leaders exploring AI-powered voice and audio solutions
  • Product managers and innovation teams assessing potential use cases
  • Government or corporate staff engaged in digital transformation efforts
 14 Hours

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