The Transcription Playbook — Copy-Paste Code for OpenAI’s New gpt-transcribe & gpt-live-transcribe (Plus the Torture-Test Results)

The companion to the full video. OpenAI shipped two new transcription models on July 28, 2026 — gpt-transcribe ($0.0045/min, 25% cheaper than Whisper) and gpt-live-transcribe (low-latency live captions) — and I spent day one torturing them with real medication names, order codes, phone numbers and audio buried under noise twice as loud as the voice. This playbook is everything that survived, ready to run tonight. INSIDE: (1) BUILD 1 — FILE → TRANSCRIPT: the complete 15-line Node script (no dependencies), plus the prompt/keywords/languages context parameters that finally make transcripts spell your product names right — my receipt: OpenAI's own 2-minute launch film transcribed for one cent. (2) BUILD 2 — LIVE CAPTIONS: the full WebSocket session script (words land under a second behind speech in my logged run) plus the delay dial explained — minimal to xhigh, which to pick for captions vs notes. (3) BUILD 3 — SPEAKER LABELS: diarized_json in 12 lines, plus the feature almost nobody noticed — known_speaker_references, where one 5-second sample of your voice puts YOUR NAME on your lines in every future transcript. (4) THE TORTURE TEST, UNEDITED — the full results table: Whisper hallucinating 'Don't forget to subscribe' on buried audio, gpt-transcribe returning an honest empty string on the same file, and the trap: keywords + extreme noise producing a fluent, completely fabricated support call — plus the three keyword safety rules that keep the model honest. (5) THE DECISION MATRIX & COST TABLE — which of the four models for which job (whisper-1 is still the one for SRT/VTT subtitles), the verified pricing against Otter's $16.99/1,200-minute cap ($5.40 raw), and the one-line whisper-1 migration with its language→languages gotcha. Every API response quoted verbatim from real calls on July 29, 2026. Independent playbook from Hyperautomation Labs — not affiliated with OpenAI or Otter.ai.

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