The fifteen problems · 11 of 15 · speech

ASR gets proper nouns wrong; the chyrons have them spelled right

Ethiopian news video is dense with Fidel chyrons, lower-thirds and headline cards. OCR of those frames yields correctly spelled names, places and organization titles, which is precisely what ASR gets wrong and precisely what a knowledge graph is made of. Designed on 24 July, never executed.

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The load-bearing design insight, stated on 24 July 2026 and never executed. Ethiopian news video is dense with Fidel chyrons, lower-thirds and headline cards. OCR of those frames (commercial OCR services support Amharic) yields correctly spelled names, places and organization titles, which is precisely what ASR gets wrong and precisely what a knowledge graph is made of.

Proposed pipeline:

Video in; ffmpeg produces scene-change frames and the audio track.
OCR the frames to an entity list.
Feed audio plus entity list plus timestamps to the Amharic speech model.
A control run of raw video straight into a multimodal model, to see whether the decomposition earns its keep.

× What it broke

Nothing; it never ran. The six frames in quarantine are the first execution of the ffmpeg step. The OCR step never ran.

✓ What it established

A way to get the part of a transcript a graph needs (names) from the part of the video that has them spelled correctly, with ASR reduced to filling in the words between.

2026-07-24 (video/OCR pipeline designed) · staging/quarantine/youtube-channels/ (six frames) · build report §4.11 · retrieved 2026-08-21

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Published August 22, 2026 at 15:13 UTC. Last updated August 22, 2026 at 17:15 UTC. Times come from this page's revision history and can be checked against it.