Convert Video to Text

Transkio accepts video files directly — MP4, MOV, WebM, MKV, and MPEG — and extracts the audio track internally before transcribing, so there's nothing to pre-process. File size limits scale with your plan to match how large video actually gets: 100MB on the free plan, up to 8GB on Ultra, which covers a full-length screen recording saved at high quality.

Because every line of the resulting transcript carries a timestamp tied to the original video, the text and the footage stay in sync automatically — click a line in the editor and the video player jumps to that exact moment, which makes reviewing a long recording, finding a specific quote, or checking a transcribed line against what was actually said on screen fast instead of tedious.

That same timestamp data is what makes exporting to SRT or VTT genuinely useful for video rather than just a formatting exercise: the caption blocks line up with the footage because they were generated from it in the first place, not typed out separately and hoped into alignment.

Webinars are one of the most common sources of long video files that need transcribing, usually because the content is genuinely valuable but locked inside an hour of footage nobody has time to rewatch. A transcript turns that hour into a document that can be skimmed, searched for a specific topic, and repurposed into a blog post or a set of key takeaways without anyone sitting through the recording again.

Online course creators use video transcripts two ways: as accessible text alongside each lesson (useful for learners who prefer reading, and for search engines indexing course content), and as raw material for writing lesson summaries or supplementary notes. YouTube creators transcribe finished videos before publishing to write better descriptions, pull out quotable lines for social clips, and generate captions that improve watch time for viewers who watch with sound off.

Vloggers and other video-first creators use transcripts less for accessibility and more for speed — turning one long recorded video into several pieces of written content (a newsletter, a caption, a thread) is far faster starting from a clean transcript than from rewatching the raw footage. And any team recording internal meetings on video, rather than audio, benefits the same way a purely audio-recorded meeting would: searchable notes instead of a video nobody reopens.

Because transcription runs against the original video file, every line of text in the transcript already carries the timestamp of the moment it was spoken — there's no separate alignment step where captions drift out of sync with footage over a long recording, which is a common failure mode with manually typed captions.

That timestamp data is what SRT and VTT exports are built from: standard, timestamped subtitle formats that any video editor or web player can load and display synced to the footage. If you specifically need finished captions rather than a document transcript, the video subtitle generator page walks through that workflow directly.

The most common one is manually extracting audio before uploading when it isn't necessary — it adds a step, a tool dependency, and a chance for something to go wrong, when uploading the original video file directly gets the same result with less effort. Another is assuming a video's built-in captions (if any exist) are good enough to publish as-is; platform auto-captions are meant for live viewing, not as a finished, quotable transcript.

A third is skipping the review pass on video specifically because the source felt informal — a casual vlog or an internal demo. Informal speech (filler words, trailing sentences, quick asides) is exactly the kind of audio that benefits most from a human editing pass, since a literal transcription of natural speech often needs light cleanup to actually read well as a document.

The short version: there's usually nothing to prepare. Trimming dead air from the start or end of a long recording can shave a small amount off processing time, but it isn't required — Transkio handles a full-length file, silence included, without issue. The one thing worth checking before uploading a screen recording is that the microphone track was actually captured; some screen-recording tools default to system audio only and silently skip the microphone unless you explicitly enable it, which produces a video with no speech to transcribe at all.

For webinars and recorded meetings pulled from a platform like Zoom or Google Meet, exporting or downloading the recording as MP4 (the default on most platforms) is the simplest path — no extra export settings to configure, since Transkio reads the file as delivered.

Manually writing captions for a video — typing out dialogue and timing each caption block by hand — produces exactly the result you want, but it's genuinely slow: a professional captioner typically budgets several times the video's runtime to caption it properly, which is why captioning is often the most expensive line item in a video production budget.

Platform auto-captions solve the speed problem but not the quality one: they're generated for live viewing, without reliable punctuation, without speaker separation, and often without a way to export the captions as a standalone file at all — useful for accessibility compliance in the moment, not for producing a document or clean subtitle file you'd actually publish.

Transkio's approach sits in between: automated like platform captions, but structured like a real transcript — punctuated, timestamped, speaker-labeled where relevant, and editable before export. It won't match a professional captioner's accuracy on genuinely difficult audio (heavy accents, dense technical jargon, overlapping dialogue), but for typical webinars, demos, and recorded meetings it gets most of the way there in minutes rather than days, with the editor there to close the gap.

Some video files — particularly from professional recording setups — contain more than one audio track, such as a separate track per speaker in a panel or podcast-style video recording. Transkio transcribes the audio track it's given; if a video has multiple audio tracks and you need a specific one transcribed, exporting or flattening to the track you want beforehand ensures the right audio is what gets processed.

For most everyday recordings — webinars, screen captures, single-camera interviews — this isn't a concern at all, since there's normally just one audio track carrying all the speech. It mainly comes up with recordings produced by dedicated video production software or multi-camera setups.

Screen recordings — a demo walkthrough, a bug report, a how-to for a piece of software — are a specific and common category of video upload, usually made with a screen-capture tool like QuickTime, Loom, or OBS, and usually narrated by a single voice explaining what's happening on screen. These transcribe especially well: one speaker, typically close to the microphone, without the room noise a video shot with a camera can pick up.

For product and support teams, transcribed screen recordings turn into documentation almost directly — the narration already describes the steps being shown, so a lightly edited transcript often works as a standalone written walkthrough alongside or instead of the video itself.

A growing number of podcasts and interviews are recorded on video, not just audio — a video call, a studio setup with cameras, or a livestream later saved as a file. Transcribing these the same way as any other video means the video-first workflow doesn't need a separate audio-extraction step before the words become usable text.

Speaker detection matters just as much for video interviews as for audio ones, so the Elite plan and up applies identically — each participant's turns are separated automatically, whether the source was a video call or an audio-only recording.

Videos exported from editing software — Premiere, Final Cut, DaVinci Resolve, or a simpler tool — come out as one of the same standard container formats already covered here (MP4 typically, sometimes MOV), so a finished export uploads and transcribes the same way as a raw recording straight off a camera or screen-capture tool. There's no export setting to worry about specifically for transcription purposes; whatever settings you'd normally use for the video's intended destination work fine here too.