Pepys

The Best Transcription Software for Qualitative Research

Ranked for verbatim accuracy, speaker labels, timestamps, CAQDAS-ready exports, confidentiality, and the cost of long interview archives.

Qualitative work has different demands from a meeting recap. You need transcripts faithful enough to code line by line, speaker labels you can trust across a two-hour interview, timestamps to link back to the audio, and files that drop cleanly into NVivo, ATLAS.ti, or Dedoose. Two concerns sit underneath all of that: whether the vendor trains its models on your participants' words, and what it costs to transcribe and archive dozens of long recordings on a grant budget.

None of these tools export a native NVivo or ATLAS.ti project file. In practice you export DOCX, TXT, or SRT and import that into your CAQDAS package, so the questions that actually separate them are accuracy, speaker handling, confidentiality, and price at scale. Here is how the main options compare for research use.

Disclosure: this roundup is published by Pepys, which is one of the tools ranked below.

Our stake: Pepys publishes this roundup, and Pepys is one of the tools listed. We have ranked by genuine fit for qualitative research rather than putting ourselves first, and every competitor detail here is drawn from the vendor's own public pricing and policy pages. Vendor pricing is stated as of July 2026; verify current prices before you buy.

How we judged

  • Verbatim accuracy and clean speaker labels for coding
  • Timestamps and DOCX/TXT/SRT exports that import into NVivo, ATLAS.ti, or Dedoose
  • Confidentiality: whether the vendor trains its models on your data
  • Cost for long recordings and archived study material
  • Language coverage for multilingual fieldwork

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Frequently asked questions

Can I import these transcripts into NVivo, ATLAS.ti, or Dedoose?

Yes, indirectly. None of these tools export a native CAQDAS project file, but all can produce DOCX, TXT, or SRT files that import into NVivo, ATLAS.ti, or Dedoose for coding. Check that timestamps and speaker labels survive the export format you choose.

Is AI transcription accurate enough for qualitative coding?

For clear audio it usually is, but plan to correct the transcript against the recording before coding, especially for crosstalk, accents, and specialist terms. If your method requires certified verbatim, a human service like Rev or Happy Scribe's proofreading tier is the safer route, at a much higher cost.

Which of these tools train on my data?

Otter's privacy policy states it trains its models on de-identified recordings. Pepys states it never trains on your audio or text and offers optional auto-delete. Sonix publicly commits to a zero-training policy and states it does not use customer audio, video, or transcripts to train its models. Always confirm against the current policy before submitting confidential participant data.

What is the cheapest way to transcribe many long interviews?

For AI transcription, per-hour or pay-once pricing tends to beat human services and monthly minute buckets on long recordings. Pepys sells credits that never expire, from about $1.25/hr for small top-ups to roughly $1/hr at the recommended 20-hour tier and about $0.85/hr at volume, and Rev's AI pay-as-you-go is $0.25/min. Human transcription at around $2/min is far more expensive per interview.

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