How We Optimize Conversational Latency in Enterprise Voice Agents

The Challenge of Voice Latency

Achieving low conversational turn-taking latency is a key goal in voice AI. When latency exceeds 1.2 seconds, conversation feels unnatural, leading to overlap, barge-in failures, and poor customer satisfaction.

Streaming ASR and Chunk Size Optimization

Traditional speech recognition processes audio in complete utterances, introducing delays. We stream audio packets in 80ms chunks directly to a sandboxed Whisper engine. By using speculative decoding on the stream, we transcribe words in real-time with low latency.

Parallelized LLM Inference and Speculative Generation

Instead of waiting for the full LLM completion, we stream the output token-by-token. Our orchestrator processes the first tokens immediately to kickstart the text-to-speech engine. By running custom domain adapters on lightweight weights (7B-8B), we achieve fast time-to-first-token (TTFT).

Direct Telephony Carrier Integration via SIP Trunks

We avoid intermediate API aggregators by routing audio over dedicated SIP trunks. Connecting directly to Twilio Elastic SIP or Vonage Carrier networks eliminates network hop overheads, reducing overall voice latency.