Introduction to Audio AI

• An understanding of general AI or data-related terminology
• Familiarity with digital workflows or enterprise systems

Audience

• Business leaders exploring AI-driven voice and audio solutions
• Product managers and innovation teams evaluating use cases
• Government or corporate staff involved in digital transformation

Audio AI refers to artificial intelligence technologies that interpret, analyze, generate, or interact with audio signals, including human speech, environmental sounds, and music.

This instructor-led, live training (online or onsite) is aimed at beginner-level professionals who wish to understand how AI is applied in the audio domain for business, communication, automation, and innovation purposes.

By the end of this training, participants will be able to:

• Understand what Audio AI is and how it is used in real-world settings.
• Identify different categories of audio AI tools (e.g., transcription, classification, generation).
• Explore business cases in customer service, security, compliance, and media.
• Evaluate AI tools and services suitable for enterprise audio applications.

Format of the Course

• Interactive lecture and discussion.
• Lots of exercises and practice.
• Hands-on implementation in a live-lab environment.

Course Customization Options

• To request a customized training for this course, please contact us to arrange.

Introduction to Audio AI

• Defining Audio AI and its key capabilities
• Differences between voice, sound, and speech AI
• Examples of popular tools and platforms

Categories of Audio AI Applications

• Speech recognition and automatic transcription
• Voice assistants and conversational agents
• Audio classification and event detection

Use Cases Across Industries

• Customer service and contact centers
• Media, podcasting, and education
• Security, compliance, and law enforcement

Working with Audio AI Tools (Demos)

• Live transcription using Whisper or Azure Speech
• Basic audio enhancement with AI noise reduction
• Overview of tools for voice cloning and generation

Choosing the Right Platform

• Cloud APIs vs open-source libraries
• Evaluating costs, accuracy, and scalability
• Vendor comparison: Google, Microsoft, OpenAI, ElevenLabs

Ethical and Legal Considerations

• Audio data privacy and consent
• Use of generated voices and deepfakes
• Guidelines for safe and compliant deployment

Exploration Lab: Applying Audio AI Concepts

• Hands-on exploration of transcription, noise reduction, and classification tools
• Small-group exercises: choosing a business case and mapping AI tool fit
• Team-based discussion: challenges, assumptions, and success criteria

Summary and Next Steps