Voice Bots in Action

Course Duration

Half Day

Audience

Employees of federal, state and local governments; and businesses working with the government.

Prerequisites

No prerequisites required.

Course Description

This half-day course is designed for developers, product managers, and business innovators who want to build practical skills in voice-enabled AI technologies. The course provides a step-by-step guide to creating a voice bot that interacts naturally with users, similar to assistants like Alexa or Siri. Participants will gain hands-on experience with speech recognition, natural language processing, and response generation, ending with a working voice bot prototype you can test.

Learning Objectives

• Get Started with Voice Bots: Understand the basics of voice bot technology and how popular systems like Alexa and Siri work.
• Voice Recognition Basics: See how voice recognition turns speech into text and how to use it in your own projects.
• Integrating Natural Language Processing (NLP): Use natural language processing to interpret what users say and generate useful responses.
• Developing a Conversational AI: Explore how to design a bot that feels more natural and human when talking with people.
• Create Your First Bot: Go step by step through building a simple voice bot.
• Make It Your Own: Customize bot interactions to match business goals or personal needs.
• Find New Uses: Identify opportunities to apply voice AI in customer service, operations, and user experiences.

Course Outline

• Recognize common use cases for Voice AI
• Define intents and slots
• Understand challenges unique to spoken interaction
• Explain the main pipeline stages
• Compare rule-based vs LLM-driven NLU
• Recognize real-world interaction challenges
• Add new intents to the pipeline
• Capture slots for functional use
• Connect to external APIs and deliver testable bot behaviors
• Apply user-centered design to voice interfaces
• Explore personalization strategies
• Design fallback and error recovery patterns
• Enhance speech quality using external providers
• Implement safety guardrails
• Identify ethical risks and data protection needs
• Explore upcoming trends in voice AI
• Identify opportunities for innovation in real products and services