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Course Outline

Introduction to Audio AI

  • Defining Audio AI and outlining its core capabilities
  • Distinguishing between voice, sound, and speech AI
  • Showcasing 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 production, podcasting, and educational platforms
  • Security, compliance, and law enforcement applications

Working with Audio AI Tools (Demos)

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

Selecting the Appropriate Platform

  • Comparing Cloud APIs with open-source libraries
  • Evaluating factors such as costs, accuracy, and scalability
  • Vendor comparison: Google, Microsoft, OpenAI, and ElevenLabs

Ethical and Legal Considerations

  • Managing audio data privacy and obtaining user consent
  • Addressing the use of generated voices and deepfakes
  • Following guidelines for 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 the suitable AI tool fit
  • Team-based discussion: addressing challenges, assumptions, and defining 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 investigating AI-driven voice and audio solutions
  • Product managers and innovation teams assessing potential use cases
  • Government or corporate staff engaged in digital transformation initiatives
 14 Hours

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