TL;DR: There are two ways to get subtitles from a video, and which one fits depends on whether the words are already on the screen. If the video already shows subtitles, OCR reads that on-screen text and keeps the exact official wording; if there are no subtitles and you only have the audio, speech recognition transcribes what is spoken. OCR wins on fidelity, speech recognition wins when no subtitle exists to read.
What is the difference between OCR and speech recognition?
The two approaches solve the same goal — a subtitle file from a video — but they look at completely different parts of the video. OCR (optical character recognition) reads text that is already visible on screen, such as burned-in subtitles, and does it frame by frame. Speech recognition (ASR) ignores the picture entirely and listens to the audio, transcribing the spoken words into text.
That is the whole distinction: one reads pixels, the other listens. Everything else — which one is more accurate, which one you should reach for — follows from whether the words you want are already printed on the picture or only exist as sound. OCR reads text off the screen frame by frame; speech recognition transcribes the audio — one reads pixels, the other listens.
When should I use OCR?
Use OCR when the video already has subtitles burned into the picture. This is the everyday case with downloaded dramas, variety shows, concert clips, and re-encoded videos where you can clearly see the captions but there is no separate subtitle file.
Because OCR reads the official on-screen text, it preserves the exact wording, names, and specialist terms that a human subtitler already wrote — nothing is guessed. If the on-screen line says a particular character name or a piece of jargon, OCR copies it as printed. When a video already carries subtitles, OCR is the accurate route because it copies the official on-screen wording exactly, instead of re-deriving it.
When should I use speech recognition?
Use speech recognition when there are no subtitles on screen and you only have the audio — an interview, a podcast recording turned into video, a raw camera clip, a lecture. There is no text to read, so the only way to get a subtitle is to generate one from scratch out of the sound.
Quality depends on the language and how clean the audio is. Clear speech in a well-supported language transcribes well; unusual names, jargon, and noisy or music-heavy audio are where it makes mistakes, because it is inferring words from sound rather than copying printed text. Speech recognition is the right tool whenever no subtitle exists on screen, and a quick human check handles the names and terms it is most likely to miss.
Which is more accurate, OCR or speech recognition?
For a video that already shows subtitles, OCR of that on-screen text is more faithful than transcribing the audio. The reason is simple: OCR copies the official wording that a human already wrote, while speech recognition has to guess at what was said. When the correct answer is already printed on the picture, reading it beats re-deriving it.
That does not make speech recognition less capable — it is simply solving a harder problem. Turning sound into text, with accents, background music, and overlapping speakers, is fundamentally more error-prone than reading clean printed characters. OCR is more faithful only because it has an official text to copy; where no such text exists, speech recognition is doing the harder job of inventing the transcript from audio.
Can I do both OCR and speech recognition on a Mac?
Yes, and often the same project needs both. GeekLink does both locally on your Mac: it OCRs burned-in subtitles into an SRT for the parts that already show text, and it transcribes audio with speech recognition (Whisper) when there is nothing on screen to read. Either result can then be translated into 40+ languages, keeping the original timing.
The choice comes down to one question you can answer just by playing the video. Pick OCR when the words are on the picture, and speech recognition when they are only in the audio. If you want the deeper walkthroughs, see how OCR extracts burned-in subtitles and the Whisper transcription guide.
FAQ
Is OCR or speech recognition more accurate for subtitles?
When the video already shows subtitles, OCR is more faithful because it reads the official on-screen text; speech recognition guesses at the audio.
Can OCR make subtitles from a video with no subtitles on screen?
No — OCR needs visible text to read. With no on-screen subtitles, use speech recognition to transcribe the audio.
Why does speech recognition get names and terms wrong?
It transcribes sound, so unusual names, jargon, and noisy or music-heavy audio are hard to catch; a quick human check fixes the rest.
What is ASR?
ASR (automatic speech recognition) is the technical name for speech-to-text — transcribing spoken audio into words.
Can I use both OCR and speech recognition?
Yes — OCR for the parts that show on-screen text and speech recognition for the parts that only have audio.