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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
- Examples 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 centers
- Media, podcasting, and educational sectors
- Security, compliance, and law enforcement
Working with Audio AI Tools (Demonstrations)
- Live transcription using Whisper or Azure Speech
- Basic audio enhancement through AI noise reduction
- Overview of tools for voice cloning and generation
Selecting the Appropriate Platform
- Cloud APIs versus open-source libraries
- Assessing costs, accuracy, and scalability
- Vendor comparison: Google, Microsoft, OpenAI, ElevenLabs
Ethical and Legal Considerations
- Audio data privacy and consent management
- The use 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 fit
- Team-based discussion: challenges, assumptions, and success criteria
Summary and Next Steps
Requirements
- A foundational grasp of general AI concepts 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
- Public sector or corporate staff engaged in digital transformation initiatives
Testimonials (1)
I got to learn more about Microsoft Copilot, something that I thought was the same as chatGPT but I got to discover more exciting options that I will forever use to make my life easy.
