Building Intelligent Voice Assistants with AI Training Course

Introduction to Conversational AI

• The historical progression and evolution of voice assistants
• Core elements: ASR, NLU, Dialogue Management, and TTS
• Survey of leading platforms: Alexa, Google Assistant, and Rasa

Designing Voice Interfaces

• Fundamental principles of conversational user experience
• Modeling intents and extracting entities
• Utilizing voice design tools and mapping flows

Development with Dialogflow and Alexa

• Configuring Dialogflow agents, intents, and webhook fulfillment
• Building Alexa Skills: handling intents, slots, voice models, and endpoint connections
• Managing multi-turn conversations and session states

Creating Voice Assistants with Rasa

• Understanding Rasa architecture: NLU, Core, and Action handling
• Configuring training data and domain definitions
• Implementing custom actions, forms, and context-aware dialogues

Integrating Voice Assistants

• Connecting to API and webhook backend services
• Linking with CRMs, databases, and external applications
• Deploying assistants across web apps, IoT devices, and mobile platforms

Testing, Deployment, and Optimization

• Utilizing simulators and test scenarios for voice interactions
• Tracking usage metrics and troubleshooting conversations
• Releasing to Google Assistant, Alexa hardware, or private platforms

Security, Compliance, and Scalability

• Implementing user authentication and authorization protocols
• Addressing data privacy, GDPR compliance, and audit logging
• Managing version control and CI/CD pipelines for voice applications

Summary and Next Steps