Using Inwista SRT Files in Premiere Pro, DaVinci Resolve and Final Cut Pro

Production teams lose real hours to subtitles — and rarely to the interesting part. Some environments still write captions by hand; most now lean on the auto-captioning built into Adobe Premiere Pro, DaVinci Resolve or Final Cut Pro, and then spend the saved time cleaning up what came out: punctuation, sentence structure, awkward segmentation, names spelled three ways.

There's a better division of labour. Generate a high-quality SRT first, import it, and spend your editing-suite time on editing-suite work — timing against picture, placement, the interplay with sound. This article shows the workflow end to end, with the import steps for all three major NLEs.

(This guide covers one exit door of the complete subtitling workflow in depth.)

Why not just use the built-in auto-captions?

Fair question, and the honest answer isn't that the NLEs' speech recognition is bad — it's that recognition is the easy half of the job. The cleanup that lands on your timeline afterwards is linguistic: sentences without structure, punctuation guessed at, blocks segmented by pause rather than grammar, terminology inconsistent across a project.

Doing that cleanup inside an NLE — caption block by caption block, in a panel built for timing rather than text — is the slowest possible place to do it. The alternative workflow front-loads the language work where language tools live:

  • Terminology arrives correct via a glossary — client names, product names and house style applied automatically at transcription.
  • Style is tuned at the source with temperature and sentence-length settings — subtitle-shaped output instead of prose to be chopped up.
  • Structure meets broadcast standards before export: Enhance splits long blocks, breaks lines at natural pauses, inserts standard gaps and brings reading speed into the professional range — the standards platforms actually check.
  • Other languages come from the same pass — Inwista translates into 55+ languages at upload, so multi-language deliverables don't mean multiple transcription rounds.

What lands in your NLE is an SRT that needs minimal rework — and SRT is a deliberately simple, robust format that effectively every professional editing tool reads.

Step 1 — Generate the SRT in Inwista

  1. Upload the audio or video file with + New Project.
  2. Choose the language — and any settings that fit the job (glossary, temperature, sentence length).
  3. Let Inwista transcribe and structure the text; run Enhance for the broadcast-standard pass.
  4. If you want a language check first, the browser editor shows the subtitles against the video — the same review you'd do in the NLE, minus the round-trip.
  5. Export as .SRT.

Step 2 — Import into your editor

Adobe Premiere Pro

Premiere reads SRT files as text-based captions:

  1. Import the SRT via File → Import (or drag it into the Project panel).
  2. Drag the file into your timeline.
  3. The subtitles appear as individual caption items on a captions track, synchronised with the video.

From there, Premiere's caption tools handle styling and track-level adjustments — which makes it well suited to both quick social deliveries and finer-grained finishing.

DaVinci Resolve

Resolve has native subtitle import:

  1. Import the SRT into your project.
  2. Place it on a dedicated subtitle track in the timeline.
  3. Edit the captions both textually and visually from there.

Particularly convenient in productions where grade, sound and text all live in the same tool — the captions simply join the party.

Final Cut Pro

Final Cut supports SRT-based workflows directly:

  1. Import via File → Import → Captions.
  2. The subtitles land automatically on their own captions lane.
  3. Adjust text and appearance in the Inspector panel.

What changes when the SRT arrives clean

When captions come in with correct punctuation, sound sentence structure and natural language from the start, the most time-consuming category of rework simply doesn't exist. Editing-suite time concentrates on what genuinely belongs there: timing against cuts, placement around graphics, the interplay of text with picture and sound.

The compound effect on a production is bigger than any single file suggests: predictable quality (every episode's captions meet the same standard, regardless of who edited), fewer manual corrections (and fewer of the inconsistencies that slip through them), and a materially faster path from raw material to delivered, captioned video.

One deliverable decision remains at the end — export from the NLE with captions as a sidecar file, or burned into the picture. That call depends on the destination, and we've written the decision guide.

Try it on your next edit

Inwista's free plan lets you run the whole workflow on your own material — upload, transcribe, structure, edit and export. Current limits and plan details are on the pricing page.

Generate your first SRT →

Frequently asked questions

Does Premiere Pro read SRT files natively? Yes — imported SRTs become caption items on a captions track, fully editable and stylable with Premiere's caption tools. The same applies in Resolve (subtitle tracks) and Final Cut (captions lanes).

Will the timing drift if my project uses a different frame rate? No — SRT timecodes are clock-based (hours:minutes:seconds,milliseconds), not frame-based, so the file is frame-rate agnostic. The NLE maps the times onto whatever your timeline runs at.

Should I import SRT or VTT into an editor? SRT. It's the format NLEs are built around; VTT is the web-native sibling for HTML5 players. Inwista exports both, so use SRT for the edit and keep VTT for the site.

Can I still style the captions in my NLE? Fully — the SRT carries text and timing, and appearance is styled with each editor's caption tools. If a project doesn't need an NLE pass at all, you can alternatively style and burn in directly from Inwista.

We deliver in several languages — does this scale? Yes. Choose a target language at upload and the same pass produces translated subtitles — one recording, an SRT per language, each imported like any other.

Is the built-in auto-captioning in my NLE really that much worse? The speech recognition is serviceable; the linguistic structuring is where the cleanup burden comes from. If your captions currently require a manual language pass in the NLE, that pass is the cost this workflow removes.