Subtitles for interviews

Interviews add cross-talk, accents, and names the model never saw in training data. Your workflow should protect accuracy where trust matters: identifiers, quotes, and numbers.

You will learn how to capture audio well, run transcription, fix speaker confusion without cluttering subtitles, and export files editors can actually use. You will also see when a full transcript with speaker labels beats plain SRT.

Run your interview audio or picture-synced video through the free AudioToSRT converter when you need a timed draft fast. You still verify quotes and names before publication, especially when money or reputation is on the line.

If you publish internationally, plan for translation after the English SRT is clean. Garbage in English becomes expensive garbage in every other language.

Free tool

Rather do it than read about it? Upload an audio or video file and get a timed .srt back.No signup, no payment, up to 100 MB per file.

Upload your file

Step-by-step guide

Step 1: Mic people separately when possible

Isolated tracks reduce bleed and improve recognition. If you only have a camera mic in a reverberant room, expect more errors at the edges of sentences and plan edit time accordingly. When budgets allow, a lav on the subject and a room mic for ambience can help later mixing, but transcription still wants intelligible speech first.

Step 2: Upload the best mix you have

Mono dialogue often beats stereo room tone fights when speech is centered. If stereo music swamps voice, export a temporary dialogue lift or reduce music under speech before you upload. Garbage audio produces confident-looking wrong words.

Step 3: Transcribe to SRT for video timelines

Fix names and proper nouns immediately because they propagate visually across social clips. If the interview references numbers, dates, or legal terms, slow down and verify against notes. A wrong number in captions is worse than a slightly casual paraphrase.

Step 4: Decide how you mark speakers

On-screen subtitles rarely need names on every line; long-form transcripts for editors may benefit from SPEAKER: prefixes. Pick one convention per deliverable so downstream tools do not choke on inconsistent tags.

Step 5: Tighten lines for clarity

Spoken filler may stay in transcripts but not in tight captions meant for TikTok or news sites. Match the density to the platform: short vertical video wants fewer words per second than a long YouTube interview.

Step 6: Review sensitive quotes carefully

Accuracy matters for journalism, investor updates, and legal clips. If someone pauses mid-thought, avoid merging lines in a way that changes meaning. When in doubt, re-listen with headphones.

Step 7: Share files with clear naming

Use lastname_topic_YYYYMMDD_en.srt patterns so producers stop asking which file is “final.” Zip caption and audio together for handoffs when remote editors lose track of attachments.

Tips for better subtitles

Collect name spellings before recording ends.
If people talk over each other, expect errors; manual fixes follow.
Use room tone reduction carefully to avoid metallic voice.
For bilingual interviews, pick a primary language per segment when possible.
Keep a timecoded note file for pull quotes.
Export both SRT and a readable doc if PR needs quotes.
If you publish a pull quote graphic, match caption spelling exactly to avoid Twitter fights.
When you record remotely, ask guests to disable aggressive noise gates that chop consonants.

Common mistakes

Assuming one microphone in a noisy room will transcribe perfectly Set expectations and plan edit time.
Cluttering every subtitle with speaker names A name in front of every line eats the reading time the words needed. Label only when the speaker changes and it is not obvious who is talking.
Publishing quotes without verifying risky claims An automatic transcript will happily attribute a wrong number or a misheard name to a real person. Check anything quotable against the audio before it is published.
Mixing multiple interviews into one caption file One file per recording keeps timings meaningful and makes it possible to replace a single interview later. Combined files have to be rebuilt from scratch.

FAQ

Can an SRT include speaker labels?

Only as plain text you type into the line yourself, usually as a name and colon at the start of a cue. On-screen subtitles are better off without them most of the time; a separate transcript is the right place for heavy labelling.

How does automatic transcription handle two people talking at once?

It transcribes what it can pick out and usually follows the louder voice, so crosstalk is where most of your review time goes. Recording each participant on a separate track, when the setup allows it, removes the problem entirely.

Should I remove filler words?

For on-screen subtitles, yes: um and you know cost reading time and add nothing. In a transcript that may be quoted, keep them, because trimming hesitation starts to shape what the person appears to have said.

Conclusion

Interviews reward good capture and careful proper nouns. Subtitles carry credibility. Invest in the fixes people actually read.

Upload interview audio to generate SRT, then refine before publication.

Keep a simple review checklist: names, numbers, quotes, sensitive claims, and file naming. Five minutes of discipline beats a public correction thread.

Now on your own file

The quickest way to finish this guide is to try it on your own recording: upload it, correct any line against the audio, download the .srt.Your upload and the subtitles are deleted automatically about an hour after the conversion.