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 Duration 14 hours (2 days)

Course Outline

Overview of Audio AI

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

Application Categories of Audio AI

  • Speech recognition and automated transcription.
  • Voice assistants and conversational interfaces.
  • Audio classification and event identification.

Industry-Specific Use Cases

  • Customer support and contact center operations.
  • Media production, podcasting, and educational sectors.
  • Security, regulatory compliance, and law enforcement.

Interacting with Audio AI Tools (Demonstrations)

  • Real-time transcription using Whisper or Azure Speech.
  • Fundamental audio improvement via AI-driven noise reduction.
  • Review of tools for voice cloning and audio generation.

Selecting the Appropriate Platform

  • Comparing Cloud APIs against open-source libraries.
  • Assessing expenses, precision, and scalability.
  • Vendor analysis: Google, Microsoft, OpenAI, and ElevenLabs.

Ethical and Regulatory Implications

  • Privacy and consent regarding audio data.
  • Application of synthetic voices and deepfakes.
  • Best practices for secure and compliant deployment.

Discovery Lab: Implementing Audio AI Concepts

  • Practical exploration of transcription, noise reduction, and classification utilities.
  • Group activities: selecting a business scenario and aligning it with the right AI tools.
  • Collaborative discussions: addressing challenges, underlying assumptions, and success metrics.

Recap and Future Directions

Requirements

  • A foundational grasp of general AI or data-related terminology.
  • Experience with digital workflows or enterprise systems.

Target Audience

  • Business executives exploring AI-powered 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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