You have a video in one language and an audience that reads another. Maybe it is an interview in Spanish, a product demo in German, or a webinar in Portuguese, and you want clean English subtitles that stay in sync with every word. Doing this by hand means transcribing, translating, and then nudging timecodes line by line until everything lines up. It is slow and error prone. With AI, you can go from a foreign-language video to timed English captions in a few minutes, and keep the timing intact the whole way.
Here is how the workflow goes, step by step.
Start with the source
First, get your video to the tool. You can upload the file directly, common formats like MP4 and MOV work, or you can paste a link to where the video lives. You do not need to strip out the audio first. The system reads the audio track straight from the video, so a single MP4 is all you need. From there the AI listens to the original language and produces a transcript with timestamps for every line.
Why timing is the hard part
The thing that makes subtitles feel professional is not just accurate words, it is timing. A caption that appears half a second late, or lingers after the speaker has moved on, pulls viewers out of the moment. Good subtitle files carry precise start and end timecodes for each line, and those timecodes have to survive translation. This matters because English and the original language rarely use the same number of words for the same idea. A tool that simply replaces text without respecting the original timing will leave you with captions that drift. The right approach translates each timed segment in place, so the English line inherits the exact start and end time of the original speech.
SRT versus VTT, and which to pick
When you export, you will usually choose between two formats. SRT, the SubRip format, is the most widely supported and works almost everywhere, from video editors to YouTube to social platforms. WebVTT, the VTT format, is the web standard used by the HTML5 video player and supports styling and positioning, so it is the better choice when you embed video on your own site. Both are plain text files you can open and tweak in any editor. A practical rule: use SRT for uploads to third-party platforms, and VTT when you control the player on your own pages.
This is the workflow RealtimeVoiceKIT is built around. You upload a video or paste a URL, and it returns a transcript with automatic speaker labels, word-level timestamps, and confidence scores, then translates that transcript into English while keeping the timing intact. You can read an AI summary to get the gist before you dive in, scan the low-confidence spots to fix any names or technical terms, and export the result as a clean SRT or WebVTT file ready to attach to your video. Because the translation respects the original segment timing, the English captions land exactly when each person speaks.
A few tips before you publish. Skim the translated lines once, especially proper nouns, brand names, and numbers, since those are where any transcription tool benefits from a quick human eye. Keep lines short enough to read comfortably, roughly two lines of forty characters is a good ceiling. And if your video has multiple speakers, the speaker labels make it easy to confirm the right words are attributed to the right person before you ship the file.
Once your English SRT or VTT is ready, publishing is simple: attach the file when you upload to a platform, or reference the VTT from your own video player. Suddenly a video that only reached one language audience is open to viewers everywhere, with captions that are searchable, accessible, and timed to the frame.
The easiest way to see it work is to try it on a real clip. RealtimeVoiceKIT offers a free plan with 10 minutes per month, including speaker labels and subtitle export, with no credit card required. Upload a foreign-language video, get timed English captions back, and judge for yourself. When you need more, the Premium plan at $4.99 a month unlocks more minutes, translation across more than 100 languages, and the full developer API.
The RealtimeVoiceKIT team writes about audio, AI, and the workflows that turn recordings into reach for the RealtimeVoiceKIT team.