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 Duration 14 hours (2 days)

Course Outline

Introduction to Audio AI

  • Defining Audio AI and its core capabilities
  • Distinguishing between voice, sound, and speech AI
  • Illustrations of widely used tools and platforms

Categories of Audio AI Applications

  • Speech recognition and automated 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

Utilizing Audio AI Tools (Demonstrations)

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

Selecting the Appropriate Platform

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

Ethical and Legal Implications

  • Privacy and consent considerations for audio data
  • Usage of generated voices and deepfakes
  • Best practices for safe and compliant deployment

Exploration Lab: Implementing Audio AI Concepts

  • Practical exploration of transcription, noise reduction, and classification tools
  • Group exercises: selecting a business scenario and mapping suitable AI tools
  • Team discussions: addressing challenges, assumptions, and success metrics

Recap and Future Directions

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 personnel engaged in digital transformation initiatives

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