Lilly Tech Systems
Designing Voice AI Systems
Build production-grade voice assistants, IVR systems, and voice-enabled applications from scratch. This course covers the complete voice pipeline — from speech recognition and text-to-speech to dialog management, telephony integration, and real-time audio streaming. Every lesson includes production code, architecture patterns, and latency optimization strategies used by teams shipping voice products at scale.
Course Lessons
Follow the lessons in order or jump to any topic you need.
1. Voice AI Architecture
Voice pipeline overview (ASR → NLU → Dialog → TTS), streaming vs batch processing, latency requirements, and build vs buy comparison.
2. Speech-to-Text Pipeline
ASR models (Whisper, Deepgram, Google STT), streaming transcription, noise handling, speaker diarization, and custom vocabulary.
3. Text-to-Speech Pipeline
TTS engines comparison (ElevenLabs, Azure TTS, Google TTS, XTTS), voice cloning, SSML, streaming audio output, and emotional speech.
4. Voice Dialog Management
Turn-taking, barge-in handling, silence detection, confirmation patterns, voice-specific UX, and error recovery strategies.
5. Telephony & IVR Integration
SIP/WebRTC integration, Twilio/Vonage architecture, call flow design, DTMF handling, call transfer, and compliance.
6. Real-Time Audio Streaming
WebSocket audio streaming, audio buffering, end-to-end latency optimization (<500ms), concurrent call handling, and edge deployment.
7. Best Practices & Checklist
Voice UX design principles, testing voice systems, accessibility, production readiness checklist, and comprehensive FAQ.