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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 centers
- Media, podcasting, and education sectors
- Security, compliance, and law enforcement
Interacting with Audio AI Tools (Demonstrations)
- Live transcription using Whisper or Azure Speech
- Fundamental audio enhancement via AI noise reduction
- Introduction to tools for voice cloning and generation
Selecting the Appropriate Platform
- Comparing Cloud APIs with open-source libraries
- Assessing costs, accuracy, and scalability
- Vendor analysis: Google, Microsoft, OpenAI, ElevenLabs
Ethical and Legal Implications
- Privacy and consent regarding audio data
- Utilization of generated voices and deepfakes
- Protocols for secure and compliant deployment
Practical Lab: Applying Audio AI Principles
- Hands-on investigation of transcription, noise reduction, and classification tools
- Group exercises: selecting a business case and aligning it with suitable AI tools
- Team discussions: addressing challenges, assumptions, and success metrics
Wrap-up and Future Actions
Requirements
- Basic familiarity with general AI or data-related terminology
- Experience 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 staff 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.
