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Course Outline

Introduction to Audio AI

  • Defining Audio AI and its core capabilities.
  • Differentiating between voice, sound, and speech AI technologies.
  • 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 Use Cases

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

Working with Audio AI Tools (Demonstrations)

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

Selecting the Appropriate Platform

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

Ethical and Legal Considerations

  • Audio data privacy and consent requirements.
  • Implications of generated voices and deepfakes.
  • 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 AI tool suitability.
  • Team-based discussion: 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 personnel involved in digital transformation initiatives.
 14 Hours

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