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Course Outline
Introduction to Audio AI
- Defining the core concepts and key capabilities of Audio AI
- 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
Use Cases Across Industries
- Customer service and contact center operations
- Media production, podcasting, and education
- Security, compliance, and law enforcement
Working with Audio AI Tools (Demonstrations)
- Real-time transcription using Whisper or Azure Speech
- Basic audio enhancement through AI-powered noise reduction
- Overview of tools for voice cloning and generation
Selecting the Appropriate Platform
- Comparing Cloud APIs with open-source libraries
- Assessing costs, accuracy, and scalability
- Vendor comparison: Google, Microsoft, OpenAI, ElevenLabs
Ethical and Legal Considerations
- Privacy and consent regarding audio data
- The use of generated voices and deepfakes
- Guidelines for safe and compliant deployment
Exploration Lab: Applying Audio AI Concepts
- Practical exploration of transcription, noise reduction, and classification tools
- Small-group exercises: selecting a business case and mapping appropriate AI tools
- Team-based discussion: addressing challenges, assumptions, and success criteria
Summary and Next Steps
Requirements
- Basic knowledge 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 staff engaged in digital transformation initiatives
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.
