Voice AI Development Certification

Module 1: Introduction to Voice AI

• Understanding voice AI
• Voice AI capabilities
• Voice assistants
• Voice agents
• Common business applications

Module 2: Voice AI Architecture

• Audio input layer
• Speech processing layer
• AI model layer
• Application and tool layer
• Audio output layer

Module 3: Digital Audio Fundamentals

• Audio signals
• Sample rates
• Bit depth
• Audio channels
• Common audio formats

Module 4: Audio Processing

• Audio capture
• Audio preprocessing
• Noise considerations
• Audio normalization
• Preparing speech input

Module 5: Speech-to-Text Fundamentals

• Speech recognition concepts
• Audio transcription
• Speech segmentation
• Recognition accuracy
• Speech-to-text workflows

Module 6: Building Speech Recognition Workflows

• Capturing user speech
• Sending audio
• Processing transcripts
• Handling recognition errors
• Integrating transcription

Module 7: Text-to-Speech Fundamentals

• Speech synthesis
• Voice generation
• Voice characteristics
• Speaking styles
• Audio output generation

Module 8: Building Speech Generation Workflows

• Preparing response text
• Selecting voice settings
• Generating speech
• Playing audio responses
• Managing output quality

Module 9: Conversational AI Fundamentals

• User intents
• Conversational turns
• Context
• Dialogue flows
• Natural interactions

Module 10: LLM-Powered Voice Applications

• Integrating language models
• Processing transcripts
• Generating responses
• Maintaining context
• Converting responses to speech

Module 11: Voice Prompt Engineering

• System instructions
• Voice-specific prompting
• Response length
• Conversational tone
• Prompt optimization

Module 12: Designing Natural Voice Conversations

• Short spoken responses
• Turn structure
• Follow-up questions
• Confirmation patterns
• Conversation recovery

Module 13: Real-Time Voice AI

• Real-time audio streams
• Streaming speech recognition
• Streaming model responses
• Streaming speech generation
• Real-time interaction architecture

Module 14: Voice Activity Detection

• Detecting speech
• Detecting silence
• Starting and stopping turns
• Background noise
• Turn boundary detection

Module 15: Turn-Taking and Interruptions

• Natural turn-taking
• User interruptions
• Barge-in behaviour
• Pausing responses
• Resuming conversations

Module 16: Latency in Voice AI

• Sources of latency
• Transcription latency
• Model latency
• Speech generation latency
• Improving response speed

Module 17: Voice Agent Fundamentals

• Voice agent architecture
• Goals and tasks
• Conversation state
• Tool access
• Controlled actions

Module 18: Tool Calling for Voice Agents

• Defining tools
• Tool selection
• Function arguments
• Executing actions
• Communicating results

Module 19: Integrating External APIs

• Third-party services
• Business systems
• Database queries
• API authentication
• Voice-driven workflows

Module 20: Voice AI Memory and Context

• Conversation history
• Session context
• User preferences
• Persistent information
• Context management

Module 21: Building Knowledge-Based Voice Assistants

• Knowledge sources
• Document retrieval
• Retrieved context
• Spoken answers
• Handling unavailable information

Module 22: Voice AI with RAG

• Retrieval-augmented generation
• Query transformation
• Knowledge retrieval
• Grounded responses
• Voice-based RAG workflows

Module 23: Multilingual Voice AI

• Language identification
• Multilingual transcription
• Multilingual responses
• Language switching
• Maintaining conversation context

Module 24: Telephony and Voice AI

• Telephony concepts
• Incoming calls
• Outgoing calls
• Audio streaming
• Connecting voice agents

Module 25: Designing AI Phone Assistants

• Call opening
• Identifying user needs
• Information collection
• Completing tasks
• Closing conversations

Module 26: Human Handoff

• Recognizing escalation needs
• Handoff triggers
• Transferring conversation context
• Connecting human support
• Managing transitions

Module 27: Voice AI Error Handling

• Transcription failures
• Misunderstood requests
• Missing information
• Tool failures
• Recovery responses

Module 28: Voice AI Security and Privacy

• Audio data protection
• Sensitive information
• Authentication
• Access controls
• Secure integrations

Module 29: Testing Voice AI Applications

• Conversation testing
• Audio quality testing
• Accent and speech variations
• Interruption testing
• Edge cases

Module 30: Evaluating Voice AI Performance

• Transcription quality
• Response relevance
• Task completion
• Conversation quality
• Response latency

Module 31: Monitoring and Optimization

• Conversation logs
• Error monitoring
• Latency tracking
• Usage analytics
• Continuous improvement

Module 32: Deploying Voice AI Applications

•  Production architecture
• Environment configuration
• Scaling voice sessions
• Reliability considerations
• Production monitoring