Drop an interview recording get a transcript a journalist can use.
Speaker-labelled, verbatim or clean-read, with the option to mark sections on-the-record or background. Tuned for the way reporters, podcasters, and qualitative researchers actually work.
What you get
What an interview transcript needs that a generic one doesn't.
Verbatim or clean-read
Toggle 'verbatim' to keep ums, ahs, false starts, and overlapping speech — required when you're quoting in print and need to show how something was actually said. Toggle 'clean-read' for a magazine-style transcript stripped of disfluencies.
On-the-record vs background
Mark a section as background or off-the-record before exporting and those lines render with a clear visual flag (or are stripped entirely on the public export). Useful when one transcript covers both pre-interview chat and the formal record.
Speaker labels you can rename
Diarization gives you 'Speaker 1' / 'Speaker 2' out of the box. One click in the editor renames every instance to 'Reporter' / 'Senator Park' across the whole transcript. Required when you're handing a transcript to an editor or co-author.
Multi-language interviews
Auto-detect handles a single language at a time. For English-Spanish or English-Hindi code-switching interviews, our model attempts both — accuracy on the secondary language is good but lower; verify quotes against the audio before publishing.
Why interview transcripts are different
Generic transcript vs interview-grade transcript.
✗ Generic transcription tool
Single mode, one-style-fits-all. Strips disfluencies whether you wanted them or not. No way to mark sections off-the-record. Speaker labels are ugly defaults you can't rename in bulk.
- No verbatim / clean-read toggle
- No on-the-record marking
- Hard-to-rename speaker labels
- No interview-specific exports
- Treats two-person dialog as monolith
✓ Whipscribe interview transcript
Verbatim or clean-read on demand, on-the-record / background tagging, renameable speakers, and a DOCX export that drops into your story or research write-up.
- Verbatim with disfluencies preserved
- Clean-read mode for publication
- Background sections can be hidden
- Bulk-rename Speaker 1 → Senator X
- DOCX export ready for editor handoff
Sample output
Speaker-labelled. Renameable. Verbatim-ready.
An interview transcript in clean-read mode. Toggle verbatim and the disfluencies come back; toggle background and tagged sections render with a flag.
Export
One transcript. Five clean formats.
Every paid tier exports all five. The free tier exports TXT and SRT.
Plain text
De-ummed paragraphs. Ready to paste.
SRT captions
Word-level. Every video editor reads this.
WebVTT
HTML5 player + YouTube uploads.
Show notes
Formatted with chapters and pull-quotes.
Machine-readable
Per-word timing + speaker IDs.
Pricing
Honest pricing, no surprises.
Credits never expire. Upgrade or downgrade any month. Free tier resets daily — no signup, no card.
Free
$0/forever
Try every feature for 30 minutes a day. No card.
- 30 min / day
- Speaker labels included
- TXT + SRT export
- No history retention
Pay-as-you-go
$1/hour
Best for one-off projects. Credits never expire.
- $10 minimum top-up
- Every export format
- 365-day history
- API access
Pro
$8/month
Indie creators. 100 hours / month, all features.
- 100 hours / month
- Clips + every aspect ratio
- Branded captions
- Priority queue
Team
$29/month
Teams. 500 hours / month, shared workspace.
- 500 hours / month
- Shared library
- API + MCP for Claude
- Workspace billing
FAQ
Interview transcript questions, answered.
Are these transcripts court-admissible?
No. For court-admissible transcripts you need a certified human stenographer (try Rev's human service or a court reporting firm) — they sign an attestation that the AI cannot. For journalism, research, podcasting, and internal use, AI-generated transcripts with a manual review pass are the standard.
Does verbatim mode actually keep ums and ahs?
Yes. Toggle 'verbatim' before generation and the transcript preserves filler words ('um', 'uh', 'like', 'you know'), false starts ('I think — I mean —'), repetitions, and overlapping speech (marked with brackets). Useful when you need to quote how something was said, not just what was said.
Can I handle a multi-language interview?
Auto-detect picks the dominant language and transcribes the whole file in it. For mixed-language conversations (English-Spanish code-switching is the most common), it makes a best effort on both — accuracy on the secondary language is lower than on the primary. Always verify quoted text against the audio before publishing.
Can I mark sections background or off-the-record?
Yes. In the editor, select a range, right-click → Mark Background. Tagged sections render with a visual flag in the DOCX export, or are stripped entirely on the 'public export' option. The original transcript stays intact in your library; the export reflects your tags.
How accurate is it for thick accents and field recordings?
On clean studio audio, expect 2-5% Word Error Rate. On field recordings with traffic, wind, or thick regional accents, expect 5-12%. Names, jargon, and acronyms are the most error-prone — budget time for a quick editing pass before publishing. The editor lets you fix names once and they propagate.
Can I redact a name or section before exporting?
Yes. In the editor, select a range and choose 'Redact' — the export replaces the text with [REDACTED] or a name placeholder you set. Useful for protecting sources, anonymizing research subjects, or removing a contractor's name before sharing the transcript externally.
Related
Related tools and pages.
Drop the interview. Get a transcript you can publish.
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