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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
- Illustrations 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 center operations
- Media production, podcasting, and education
- Security, compliance, and law enforcement
Utilizing Audio AI Tools (Demonstrations)
- Live transcription using Whisper or Azure Speech
- Basic audio enhancement via AI-driven noise reduction
- Overview of tools for voice cloning and generation
Selecting the Appropriate Platform
- Comparing Cloud APIs against open-source libraries
- Evaluating costs, accuracy, and scalability
- Vendor analysis: Google, Microsoft, OpenAI, ElevenLabs
Ethical and Legal Implications
- Privacy and consent considerations for audio data
- Usage of generated voices and deepfakes
- Best practices for safe and compliant deployment
Exploration Lab: Implementing Audio AI Concepts
- Practical exploration of transcription, noise reduction, and classification tools
- Group exercises: selecting a business scenario and mapping suitable AI tools
- Team discussions: addressing challenges, assumptions, and success metrics
Recap and Future Directions
Requirements
- A foundational understanding 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 personnel 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.