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Duration 14 hours (2 days)
Course Outline
Overview of Audio AI
- Defining Audio AI and its core capabilities
- Distinguishing between voice, sound, and speech AI
- Examples 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 production, podcasting, and education
- Security, compliance, and law enforcement applications
Practical Demonstration of Audio AI Tools
- Performing live transcription with Whisper or Azure Speech
- Enhancing audio quality using AI noise reduction techniques
- Overview of tools for voice cloning and synthesis
Selecting the Appropriate Platform
- Comparing cloud APIs with open-source libraries
- Assessing costs, accuracy, and scalability
- Vendor analysis: Google, Microsoft, OpenAI, and ElevenLabs
Ethical and Legal Implications
- Addressing audio data privacy and consent requirements
- Managing the use of generated voices and deepfakes
- Guidelines for safe and compliant deployment
Exploration Lab: Applying Audio AI Concepts
- Hands-on practice with transcription, noise reduction, and classification tools
- Small-group activity: Selecting a business case and aligning appropriate AI tools
- Team discussion: Addressing challenges, assumptions, and defining success criteria
Summary and Future Directions
Requirements
- Basic knowledge of general AI or data-related terminology
Audience
- Business leaders seeking AI-driven voice and audio solutions
- Product managers and innovation teams assessing use cases
- Government or corporate personnel engaged in digital transformation
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.
