Guide category
Transcription Technology
A transcript is only as good as the process that produced it. These explainers cover automatic speech recognition, Whisper versus YouTube auto-captions, multilingual sentence splitting, and how to deal with captions that are wrong or missing.
YouTube Auto Captions vs Whisper: Accuracy, Differences and Limitations
How YouTube's automatic captions and OpenAI's open-source Whisper model differ in design, punctuation, languages and failure modes — and a reproducible way to measure accuracy yourself.
How Automatic Speech Recognition Works
A plain-language explanation of how speech becomes text: audio features, acoustic and language modelling, end-to-end models like Whisper, decoding, and why errors happen.
How to Transcribe Videos in Different Languages
How to get an accurate transcript when a video is not in English: finding the original caption track, avoiding accidental translation, handling mixed languages, and using speech recognition.
How Sentence Splitting Works in Multilingual Transcription
Captions arrive as short timed fragments. This explainer shows how fragments are de-duplicated and merged into sentences and paragraphs across Latin, Bengali, Devanagari and Arabic scripts.
How to Fix Incorrect YouTube Captions
Why auto-captions mishear names, numbers and technical terms, how to correct a transcript efficiently, and what creators can do to fix captions at the source.
How to Fix Missing or Unavailable YouTube Captions
Every common reason a video shows no transcript — disabled captions, live streams, new uploads, regional limits, rate limiting — and what you can do in each case.
Understanding Transcript Languages, Tracks and Timestamps
Manual vs auto-generated tracks, auto-translated captions, language codes like en-GB and bn, and how caption timestamps are measured — the background you need to trust a transcript.