AI SummaryTranscribe audio and video files to text with optional speaker identification and diarization. Useful for developers building transcription features, interview processing tools, or meeting documentation systems.
Install
# Add to your project root as SKILL.md curl -o SKILL.md "https://raw.githubusercontent.com/openai/skills/main/skills/.curated/transcribe/SKILL.md"
Description
Transcribe audio files to text with optional diarization and known-speaker hints. Use when a user asks to transcribe speech from audio/video, extract text from recordings, or label speakers in interviews or meetings.
Audio Transcribe
Transcribe audio using OpenAI, with optional speaker diarization when requested. Prefer the bundled CLI for deterministic, repeatable runs.
Workflow
• Collect inputs: audio file path(s), desired response format (text/json/diarized_json), optional language hint, and any known speaker references. • Verify OPENAI_API_KEY is set. If missing, ask the user to set it locally (do not ask them to paste the key). • Run the bundled transcribe_diarize.py CLI with sensible defaults (fast text transcription). • Validate the output: transcription quality, speaker labels, and segment boundaries; iterate with a single targeted change if needed. • Save outputs under output/transcribe/ when working in this repo.
Decision rules
• Default to gpt-4o-mini-transcribe with --response-format text for fast transcription. • If the user wants speaker labels or diarization, use --model gpt-4o-transcribe-diarize --response-format diarized_json. • If audio is longer than ~30 seconds, keep --chunking-strategy auto. • Prompting is not supported for gpt-4o-transcribe-diarize.
Output conventions
• Use output/transcribe/<job-id>/ for evaluation runs. • Use --out-dir for multiple files to avoid overwriting.
Quality Score
Good
81/100
Trust & Transparency
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