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Course Outline
Introduction to Audio AI
- Defining Audio AI and its core capabilities
- Distinguishing between voice, sound, and speech AI
- Reviewing examples of well-known 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 center operations
- Media, podcasting, and educational sectors
- Security, compliance, and law enforcement contexts
Interacting with Audio AI Tools (Demonstrations)
- Live transcription using Whisper or Azure Speech
- Fundamental audio enhancement via 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 Perspectives
- Privacy and consent regarding audio data
- Implications of using generated voices and deepfakes
- Protocols for safe and compliant deployment
Exploration Lab: Implementing Audio AI Concepts
- Practical exploration of transcription, noise reduction, and classification tools
- Small-group activities: selecting a business case and aligning AI tool compatibility
- Collaborative discussion: addressing challenges, assumptions, and success metrics
Conclusion and Recommended Next Steps
Requirements
- Familiarity with general AI or data-related terminology
- Understanding of 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 personnel 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.