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Duration 14 hours
Course Outline
Fundamentals of Audio AI
- Defining Audio AI and its primary capabilities
- Distinguishing between voice, sound, and speech AI
- Illustrations of widely used tools and platforms
Types 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 agencies
Utilizing Audio AI Tools (Demonstrations)
- Live transcription using Whisper or Azure Speech
- Basic audio enhancement through AI noise reduction
- Overview of tools for voice cloning and generation
Selecting the Optimal Platform
- Cloud APIs compared with open-source libraries
- Assessing costs, accuracy, and scalability
- Vendor comparison: Google, Microsoft, OpenAI, ElevenLabs
Ethical and Legal Implications
- Audio data privacy and consent management
- Utilization of generated voices and deepfakes
- Guidelines for secure and compliant deployment
Exploration Lab: Implementing Audio AI Concepts
- Practical exploration of transcription, noise reduction, and classification tools
- Small-group exercises: selecting a business case and aligning AI tool fit
- Team-based discussion: addressing challenges, assumptions, and success criteria
Recap and Future Directions
Requirements
- Basic knowledge of general AI or data-related terminology
- Awareness 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 staff participating 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.