Real-Time Voice AI Platform

The problem

The project explores how conversational voice AI can operate as a real-time system rather than a conventional sequential speech pipeline. The current implementation focuses on establishing reliable low-level audio transport, bounded concurrency and testable runtime foundations.

Build and validate the technical foundations for a responsive real-time voice system, keeping latency, memory ownership, interruption handling and system safety explicit architectural concerns.

The challenges

• ●Designing the audio path around bounded memory and predictable execution needed deliberate ownership, queueing and concurrency decisions rather than generic application patterns.
• ●Real-time interruption and streaming behaviour has to be coordinated across audio transport, session state and generation boundaries, without letting stale work reach playback.
• ●Probabilistic model output and deterministic control are separated by design, so actions and critical values pass a validation boundary before they take effect.

The solution

• ●Core C++ audio primitives: PCM validation, audio frame handling, jitter buffering and fixed-capacity SPSC queues.
• ●A working TCP/WebSocket listener feeding incoming PCM audio into the real-time processing path.
• ●Deterministic ASR and TTS test doubles, so the pipeline can be exercised without waiting on model integrations.
• ●Bounded per-producer media queues built around single-producer, single-consumer ownership.
• ●An engineering workflow of small tickets, explicit invariants and automated validation, so implementation status is evidence-based.