Emilia is an ongoing autoresearch project aiming to build a state-of-the-art detector for AI-generated audio. For the past few weeks, Codex and OpenAI’s latest models have helped direct experiments, evaluate results, and iterate on the detector. For this hackathon, I built and shipped a native Mac app that brings the current Emilia detector into live conversations. It listens through the microphone or system audio and displays a click-through amber indicator when it detects synthetic-voice evidence. OpenAI Whisper or Realtime transcribes the conversation, and GPT-6 Astra combines the transcript with recent voice evidence to identify scam warning signs. Suspicious context triggers a red border and a warning grounded in the caller’s words. The distinction matters: an automated appointment reminder can produce amber without red, while a synthetic voice claiming to be your daughter can prompt a warning to verify the caller. The app, source code, and signed, notarized download are public. Emilia’s research predates the hackathon; the native app and live integrations were built during the event. Because the research uses rights-restricted data, we are not distributing the Emilia checkpoint. The public download instead includes a clearly labeled AASIST-L baseline; the demo uses actual Emilia v8.
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