This is a beast of a question and I did not pace myself well.
Start by clarifying requirements (e.g., use case, scale, latency targets) and then walk through the end-to-end pipeline stage by stage, highlighting key design decisions and trade-offs. Emphasize latency budgets, barge-in handling, scalability, and observability as critical aspects, and conclude with a summary of how the system meets the requirements.
Pro tip: Quantify latency budgets for each stage (e.g., STT 200ms, NLU 100ms, TTS 150ms) and explain how you'd handle barge-in by immediately stopping TTS and processing the new input, showing you understand real-time constraints.
Ask about expected concurrency, latency targets, use case (e.g., customer support, voice assistant), and any constraints like on-prem vs cloud. This ensures the design meets the actual needs.
Describe each component: speech-to-text (STT), intent and dialog understanding (NLU/DM), state management, response generation (NLG), text-to-speech (TTS), and audio streaming. Explain how they connect and the data flow.
Break down the end-to-end latency budget per stage, and explain techniques to minimize it (e.g., streaming STT, incremental TTS). Detail barge-in handling: detecting user speech during TTS playback, stopping playback, and processing the interruption.
Discuss scaling strategies: load balancing, horizontal scaling of stateless services, session affinity for stateful components, and using message queues for decoupling. Mention auto-scaling and resource allocation.
Outline monitoring and logging: track latency per stage, error rates, and user interactions. Use distributed tracing to debug issues, and set up alerts for anomalies.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.