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 Duration 14 hours (2 days)

Course Outline

Overview of Audio AI

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

Application Categories for Audio AI

  • Speech recognition and automated transcription processes
  • Voice assistants and conversational agent technologies
  • Audio classification and event detection mechanisms

Industry-Specific Use Cases

  • Customer service optimization and contact center operations
  • Applications in media, podcasting, and educational sectors
  • Security, compliance, and law enforcement operations

Practical Tools and Demonstrations

  • Live transcription demonstrations using Whisper or Azure Speech
  • Basic audio enhancement techniques utilizing AI noise reduction
  • Overview of tools dedicated to voice cloning and generation

Selecting the Appropriate Platform

  • Comparing Cloud APIs with open-source libraries
  • Assessing factors such as cost, accuracy, and scalability
  • Vendor comparison involving Google, Microsoft, OpenAI, and ElevenLabs

Ethical and Regulatory Implications

  • Privacy concerns regarding audio data and consent management
  • Considerations surrounding the use of generated voices and deepfakes
  • Guidelines for ensuring safe and compliant deployment strategies

Practical Lab: Implementing Audio AI Concepts

  • Hands-on exploration of tools for transcription, noise reduction, and classification
  • Group exercises focused on selecting a business case and matching it with the appropriate AI tool
  • Team discussions addressing challenges, assumptions, and defining success criteria

Course Summary and Future Directions

Requirements

  • Foundational knowledge of general AI concepts or data-related terminology
  • Basic familiarity with digital workflows or enterprise systems

Target Audience

  • Business leaders interested in 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

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