The Complete Guide to Interview and Meeting Transcription: From Recording to SRT/VTT Export

The Complete Guide to Interview and Meeting Transcription

The real work starts after the interview ends. Manually transcribing one hour of interview audio takes 4–5 hours; one meeting carries 20,000+ characters of information, and summarizing it still eats "someone's evening" in most workplaces.

This guide walks the full practical workflow: recording tips → AI transcription → editing → export to minutes/drafts/subtitles. I'll use PUBVOICE as the example tool, but most of it — recording principles, SRT vs. VTT — applies to any transcription service.

The Reality of Time and Cost

Method	Rough time	Notes
Manual transcription	4–5 hrs per audio hour	Includes relistening
Human outsourcing	Days of turnaround	~thousands of yen per hour
AI + editing	10–30 min	Fixing misrecognitions, verifying

What AI replaces is typing time, not verification time. But removing typing alone shrinks the whole job to under a tenth — that's the premise for designing the workflow.

Step 0: Recording — 80% of Quality Is Decided Here

The biggest factor in transcription accuracy is the recording, not the AI:

1. Get mics close to speakers. One phone picking up a whole room is the worst case for diarization. Put a recorder near each speaker, or arrange seating so everyone's voice lands clearly.
2. Reduce crosstalk. Simultaneous speech wrecks both recognition and speaker separation. A facilitator saying "one at a time, please" saves hours of editing later.
3. Use standard formats (mp3/m4a/wav). PUBVOICE accepts files up to 500MB and recordings over 5 hours.
4. Record a 30-second test and check that the quietest person is audible. This alone prevents most failures.

Step 1: Upload and Transcribe

In PUBVOICE: drag the file into the workspace (/transcripts), watch status update (queued → processing → done), and get a transcript with speaker labels and timestamps per segment. New users can try up to 90 seconds of audio on the top page without registering — test it with the kind of audio you actually record.

Step 2: Edit — Fix "Who Said What"

AI misrecognitions fall into three practical buckets:

• Proper nouns and jargon (company names, people, industry terms) — the most common
• Speaker assignment swaps — when speakers sit close or sound alike
• Homophone choices — fix by context

The basic flow in PUBVOICE's editor: bulk-rename speakers (Speaker 1 → "Tanaka"), then use in-document search to hunt down misrecognitions. The editor highlights segments in sync with the audio player, so "click a suspicious line, relisten, fix" happens in one place — you verify while the conversation is still fresh, which is the real advantage over outsourcing.

Step 3A: Turn It into Minutes

The key to minutes is not writing everything:

1. Pull decisions out first (that's the body of the minutes)
2. Table the TODOs (who, by when)
3. Quote background only where the trail matters, briefly, from the relevant segments
4. Close with open items and next agenda

Keep the timestamped transcript as the traceable archive; share the TXT (speaker-labeled) export as the base document.

Step 3B: Turn It into an Article

1. Rename speakers to real names, split into readable paragraphs
2. Mark the quotes you'll use — same as in the paper era
3. Order quotes to your structure and write the connective text
4. Verify numbers and proper nouns against the audio by clicking the timestamp

That last step matters most: numeric misquotes kill articles, and one-click relistening collapses the fact-check loop.

Step 3C: Subtitles — SRT vs. VTT

Format	Main use	Notes
SRT	YouTube, Premiere, Final Cut, most editors	Most widely supported. HH:MM:SS,mmm (comma)
VTT	HTML5 <video>, web players	Needs WEBVTT header. HH:MM:SS.mmm (period). Styleable
TXT (speaker-labeled)	Minutes, drafts, archives	Readable text with speakers and times

When in doubt, choose SRT — nearly every video tool reads it. For direct web embedding, use VTT. PUBVOICE exports all three from a single transcript.

Security and Handling Notes

• Consent to record: legal in Japan in principle, but telling interviewees and participants that you're recording — and why — is the professional standard (and mandatory in some industries/regions)
• Confidential material: for board/legal/HR audio, check the service's data location and retention first; mask sensitive parts during editing when external transmission is a concern
• Retention design: when transcripts serve as records, decide the retention period for source audio and transcripts up front

FAQ

Q. Does it handle long recordings (2–3 hour lectures)?
A. Yes — files up to 500MB, with speaker separation that keeps Q&A sections attributed.

Q. How about dialects and non-standard speech?
A. Standard Japanese yields the best accuracy; dialects, fast speech, and mumbling increase errors — which is why Step 0 matters most there.

Q. What about English and other languages?
A. Processable, but current optimization is Japanese-first. If multilingual is your main use case, consider multilingual services like Notta from the comparison article.

Q. Can I share results with my team?
A. Exported TXT/SRT/VTT files share as-is. For minutes operations, the standard pattern is a summary (decisions + TODOs) for circulation plus the timestamped full text as the record.

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• AI Transcription Market: An Analyst's Breakdown
• AI Transcription Services Compared (2026)