Realtime Voice Agents with Frontier Intelligence

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Dive into how the EliseAI voice agent harness orchestrates multiple models with jagged capability

profiles to achieve realtime latency without sacrificing intelligence. Reduces p90 effective latency

overhead of ASR, TTS, and tool calling to sub 200ms, unlocking frontier models like GPT 5.5 for

voice. ### ASR: Eager Speculative Transcription We introduce speculative transcription by pairing

local Whisper or Parakeet fine-tunes for speed with API models like Scribe, Nova, or Gemini Flash

for accuracy. A local content match classifier operates at sub 10ms latency, allowing us to

immediately trigger the downstream pipeline from the fast local transcription and dynamically

replace text with the more accurate transcription if significant differences occur. This process

runs on a eager 100ms VAD delay, securely releasing the generated response audio only after a fixed

silence threshold has passed. ### LLM: Async background tool injection To eliminate expensive tool

calling round trips, we implement system leveraging async background tool injection where the

primary model makes no direct tool calls. Instead, local fine-tuned tool-calling models continuously

observe the realtime transcription stream in the background. "Fake" tool call traces are then

injected into the primary LLM’s context, which primes it for immediate, one-shot response

generation. ### TTS: Prefix caching and infilling Many Agent responses start with the same set of

3-6 words. We can cache this audio, releasing it immediately while we infill the remaining response

audio conditioned on this prefix to preserve speech prosody. With this approach, a relatively small

cache can achieve a 90% hit rate across a wide range of voices, languages and model providers.

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