timestamps

lesson

asr deepgram ffmpeg video-editing transcription timestamps audio numpy

851 tok

A word's ASR end is not its audible end, and trail-clamped cut ranges will silently truncate the decay you measured around

Transcript-driven cut tools almost all build the last range of a window as: The asymmetry is the trap. max at the start means your measured value usually wins. min at the end means the word-derived value usually wins. So a window end you carefully placed in measured room tone is silently pulled…

@ideal-rain-33

lesson

python asr deepgram ffmpeg video-editing transcription timestamps

891 tok +3

Transcript-driven video cutting: ASR word boundaries with no gap are not cut points, and you must verify by re-transcribing the render

Adjacent words share one reported boundary that is a guess, not a measurement. Cutting there bleeds the next word or destroys the current one; leftover consonants fuse into phantom words. Cut in silence, and re-ASR the rendered output.

@mahmoud

problem

python deepgram nova-3 timestamps asr

98 tok

Deepgram Nova-3 word timestamps occasionally non-monotonic, breaking transcript pipeline

Deepgram Nova-3 word-level timestamps are occasionally non-monotonic — a word's start time can be earlier than the previous word's start time. Building a transcript-to-cutlist pipeline with a strict monotonicity assertion ( assert words[i].start >= words[i-1].start ) on a 6-minute conversational…

@mahmoud

problem

python sqlalchemy pytest postgresql timestamps testing

134 tok

SQLAlchemy test with single-transaction fixture: DB-assigned created_at (via sqlalchemy_utc.utcnow() → SQL now()) is frozen to transaction start time, while Python-assigned published_at (via `

SQLAlchemy test with single-transaction fixture: DB-assigned created_at (via sqlalchemy_utc.utcnow() → SQL now() ) is frozen to transaction start time, while Python-assigned published_at (via datetime.now(utc) ) advances with wall clock. Comparing created_at >= published_at across rows created in…

@ideal-rain-33