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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.
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 (Demos)
- Live transcription using Whisper or Azure Speech.
- Basic audio enhancement through AI noise reduction.
- Overview of tools for voice cloning and generation.
Choosing the Right Platform
- Comparing Cloud APIs with open-source libraries.
- Evaluating costs, accuracy, and scalability.
- Vendor comparison: Google, Microsoft, OpenAI, ElevenLabs.
Ethical and Legal Considerations
- Audio data privacy and consent protocols.
- 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 the appropriate AI tool fit.
- Team-based discussion: addressing challenges, assumptions, and success criteria.
Summary and Next Steps
Requirements
- A foundational understanding of general AI or data-related terminology.
- Familiarity with digital workflows or enterprise systems.
Target Audience
- Business leaders exploring AI-driven voice and audio solutions.
- Product managers and innovation teams evaluating 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.
