Automate Video Captioning and Subtitle Generation
A video gets published without captions because captioning was treated as a nice-to-have add-on rather than a required publishing step, and it stays that way until someone with a hearing impairment, a viewer scrolling silently on a train, or a compliance review flags the gap. When captions do get added, they're often auto-generated by the platform's default tool with no review, producing garbled technical terms, misattributed speakers in a multi-person interview, and timing that drifts out of sync by the video's midpoint — which is arguably worse than no captions at all, since it actively misrepresents what was said.
STARTING PRICE
From €99
Starter tier · Single-workflow automation, one core integration, fast turnaround.
Get a quote →Saves roughly 1-3 hrs per video in manual caption creation and correction.
How the automation works
We generate captions for every video at the point of publishing rather than as an afterthought, with a review pass that catches and corrects the failure modes automatic transcription reliably gets wrong — technical or brand-specific terminology, speaker identification in multi-person content, and timing drift in longer videos. Where content needs to reach a non-English audience, translated subtitles are generated from the corrected English caption file rather than transcribed independently, so translation quality inherits the corrections rather than repeating the same errors in a different language. Captions are delivered in the format each publishing platform requires, checked for sync accuracy before the video goes live.
Process flow
- 01
Video submitted for publishing trigger
A finished video is submitted to the publishing queue, triggering caption generation as a required step before the video is marked ready to publish.
- 02
Generate initial transcript and caption timing ai
An initial transcript with caption timing is generated from the video's audio track, including a first-pass attempt at speaker labeling for multi-person content.
- 03
Correct technical and brand terminology ai
Technical terms, product names and brand-specific language are checked against a maintained glossary and corrected, since generic transcription models reliably mis-transcribe specialized vocabulary.
- 04
Generate translated subtitles from corrected captions ai
Where translated subtitles are needed, they're generated from the corrected English caption file rather than an independent transcription pass, so translation inherits the terminology corrections instead of repeating the same errors.
- 05
Sync accuracy check before publish output
Caption timing is checked for drift across the full video length before publishing, catching the common failure where captions start in sync but drift out of alignment by the video's later sections.
Inputs
- Source video file
- Brand and technical terminology glossary
- Target languages for translated subtitles
- Platform-specific caption format requirements
Outputs
- Speaker-labeled caption file
- Terminology-corrected transcript
- Translated subtitle files
- Sync accuracy check report
Works with
Prefer a fully custom build instead of an off-the-shelf integration? We scope both options during your free consultation — most jobs like this one work fine on standard connectors, but higher-volume or non-standard systems sometimes need bespoke API work, reflected in the complex tier.
Where this goes wrong if you get it wrong
- Auto-generated captions handle overlapping speech in a multi-person interview or panel discussion poorly, often merging two speakers' words into one garbled line or attributing one speaker's words to another — this needs explicit review on any multi-speaker content, not just a spot-check on single-narrator videos.
- Caption timing that's accurate at the start of a video can drift progressively out of sync by the later sections, especially in longer content or content with pauses and non-speech audio, so sync needs checking across the full video length, not just the opening minute where most manual reviews stop looking.
- Translated subtitles generated by directly machine-translating the English caption file without adjusting for target-language reading speed can produce subtitles that flash past too quickly to read, since some languages require more characters to express the same meaning, and subtitle timing needs adjustment per target language, not a uniform pace across all translations.
- Regulatory accessibility requirements for captioning (varying by jurisdiction and industry, particularly for public-facing organizations) often specify minimum accuracy standards beyond what a purely automated, unreviewed caption file reliably achieves, so a compliance-driven captioning need should include the terminology and sync review steps, not rely on default automated output alone.
Frequently asked questions
How accurate are the captions without manual transcription from scratch?
The terminology correction and sync check steps bring automated transcription substantially closer to broadcast-quality accuracy, though genuinely accented, overlapping or noisy audio may still need a targeted manual review pass beyond the automated correction.
Can this generate captions in multiple languages from one video?
Yes — translated subtitles are generated from the corrected English caption file for each target language needed, keeping terminology consistent across languages rather than independently transcribed and translated.
Does this meet accessibility compliance requirements?
It's built to substantially improve accuracy toward common accessibility standards, though the specific compliance requirement for your jurisdiction and industry should be checked against the final output, since standards vary.
What video platforms does this work with?
Caption files are delivered in the format required by major platforms including YouTube, Vimeo and standard SRT/VTT formats for embedding elsewhere.