TranscriptFlow — YouTube Sources

From a selected video to preserved editorial source material

Updated:

From a personal tool to editorial intake

The earlier TranscriptFlow experiment sent YouTube transcripts to Notion. The current implementation lives in the KSNK Media publishing workflow as youtube-postgres.

The current workflow

  1. I select a YouTube URL for processing.
  2. The service preserves the original audio and prepares it for speech recognition.
  3. Transcription jobs retain their responses and processing history, so a saved result does not need to be recognised again.
  4. Verified source material is registered in the Hub editorial store, with its files and hashes.

A transcript is source material. It does not automatically become an approved article, a translation or a publication.

What changed

PostgreSQL and source bundles replaced the earlier Notion-based route. The current design puts preservation, traceability and recovery before automatic rewriting. Ambiguous outcomes are held for review instead of being retried blindly.

Read the wider publishing case →

Python Speech recognition PostgreSQL yt-dlp ffmpeg