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Course Outline
Introduction to Audio AI
- Defining Audio AI and its key capabilities
- Differences between voice, sound, and speech AI
- Examples 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
Use Cases Across Industries
- Customer service and contact centers
- Media, podcasting, and education
- Security, compliance, and law enforcement
Working with Audio AI Tools (Demos)
- Live transcription using Whisper or Azure Speech
- Basic audio enhancement with AI noise reduction
- Overview of tools for voice cloning and generation
Choosing the Right Platform
- Cloud APIs vs open-source libraries
- Evaluating costs, accuracy, and scalability
- Vendor comparison: Google, Microsoft, OpenAI, ElevenLabs
Ethical and Legal Considerations
- Audio data privacy and consent
- 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: choosing a business case and mapping AI tool fit
- Team-based discussion: challenges, assumptions, and success criteria
Summary and Next Steps
Requirements
- An understanding of general AI or data-related terminology
- Familiarity with digital workflows or enterprise systems
Audience
- Business leaders exploring AI-driven voice and audio solutions
- Product managers and innovation teams evaluating use cases
- Government or corporate staff involved in digital transformation
14 Hours
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.