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Content of the Active Inference Journal — transcripts, metadata, captions, translations, and curated materials from the Active Inference Institute video library.
Learn more: https://activeinference.institute/learning/ · Tooling: https://github.com/ActiveInferenceInstitute/Journal-Utilities
Content is source-namespaced so other channels and non-video sources can live alongside, e.g. data/video/<other-channel>/… or data/<other-type>/<source>/…:
data/video/activeinferenceinstitute/<Series>/<item>/
metadata.json # canonical: series, item, parts[{video_id, url, title, duration, upload_date, speakers}]
transcript.txt # derived speaker-labeled text (part-tagged when multi-part)
transcript.json # raw diarized segments — immutable, SPEAKER_NN labels (where available)
captions/ # original-language .srt (+ youtube_captions.txt where captions predate diarization)
translations/ # translated .srt (per language)
assets/ # images, html, prose, appendices, bibliography, …
README.md # human nav: titles, links, contents
docs/ # technical documentation (SCHEMA.md, …)
INDEX.json # machine entry point: every item, its videos, paths
INDEX.md # human index, grouped by series
Current item and video totals are generated in INDEX.json. Deliberate duplicate records are marked with duplicate_of; the index reports both indexed video records and unique video IDs. Every Institute channel video is represented (uncategorized videos live under Other/).
Transcripts and metadata are pulled completely and idempotently from the Institute YouTube channel by Journal-Utilities. Most transcripts are WhisperX-diarized: transcript.json holds the immutable raw segments (SPEAKER_NN), human speaker identifications are recorded in metadata.json parts[].speakers, and transcript.txt is regenerated from the two (Journal-Utilities/scripts/apply_speaker_names.py). Items without diarization yet carry YouTube-caption text; original captions always remain under captions/. Private/unlisted videos are not transcribed. See docs/SCHEMA.md ("Transcripts — raw vs derived").
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