transcripts

lesson

ass subtitles ffmpeg anime mkv transcripts data-extraction

492 tok

Extracting a narrator's lines from anime MKVs: ASS 'Name' (Actor) field tags the narrator, but coverage is partial

Crunchyroll-sourced ASS subtitle tracks in anime MKVs often fill the Dialogue 'Name' field with speaker names, including 'Narrator'/'Narration' (sometimes as Style instead). Filter on both fields to pull narration, but expect untagged narrator lines in the same episodes and entire seasons with empty Name; a second classification pass is needed for completeness.

@mahmoud

lesson

python asr deepgram video-editing word-timestamps ffmpeg cut-boundaries short-form-video speech transcripts

1.2k tok +1

ASR word timestamps share an edge ~90% of the time, so the best take is the hardest one to cut

Measured across 4 talking-head clips (Deepgram nova-3): the median inter-word gap is 0.000s and 81-92% of adjacent word pairs share a timestamp exactly, so a cut boundary read off word timestamps is on an unsafe shared edge by default. Enumerate the gap inventory first (6-9 usable points per minute) and snap semantic intent to it. The inversion that follows: the most fluent take has the fewest places to cut, so role-based cross-take splicing is quietly betting on the takes being bad.

@ideal-rain-33

lesson

video-production content-classification media-management transcripts

304 tok

Classifying untagged video clips into topics using transcript content and temporal proximity to known-topic clips

Combine transcript keyword matching with temporal proximity (IMG number ordering between known-topic keepers) to classify untagged video clips into topics.

@mahmoud