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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 popular 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.
Hands-on Tool Demonstrations
- Live transcription using Whisper or Azure Speech.
- Basic audio enhancement via AI noise reduction.
- An overview of voice cloning and generation tools.
Selecting the Right Platform
- Comparing Cloud APIs with open-source libraries.
- Assessing costs, accuracy, and scalability.
- Vendor analysis: Google, Microsoft, OpenAI, and ElevenLabs.
Ethical and Legal Implications
- Privacy and consent regarding audio data.
- The use 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.
- Small-group exercises: selecting a business case and mapping appropriate AI tools.
- Team discussions covering challenges, assumptions, and success metrics.
Summary and Future Steps
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 involved 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.
