Key points at a glance
- Agree on data processing before recording.
- Minimise access to identifiable material.
- Correct speech and speaker errors against audio.
Design the process before recording
An interview can contain personal information even when the final thesis uses pseudonyms. Ask your supervisor and follow institutional rules before selecting a transcription service. Participant information should accurately describe recording, any transfer to a service, retention and access. These choices cannot be responsibly improvised after the interview.
Example: A participant names an employer and discusses a specific medical history. Uploading the raw audio to an arbitrary website may expose more information than analysis needs. Use an approved process, restrict access and consult the university privacy contact when the position is unclear. Requirements depend on the project and jurisdiction.
Record the tool’s data path
Distinguish a locally run tool from a cloud service. Check storage location, provider access, training uses and deletion settings. A generic “secure” label does not answer these questions. Avoid identifying file names when possible and keep any pseudonym key separate from the working transcript.
In the methods chapter, say what tool helped with transcription and what manual review followed. If your university requires an AI-use statement, follow its current policy. A precise process description helps readers assess how the interview material became analysable text.
Correct errors that change meaning
Speech recognition frequently mishears technical terms, dialect, overlapping voices and short replies. Replay critical passages. Mark unintelligible audio according to your transcription convention rather than inventing likely words. Pay particular attention to negations, numbers, names and statements central to your research question.
Choose your transcription level before editing: smoothed sentences or details such as pauses and fillers? A tool's polished version may be acceptable for one type of content analysis but erase cues needed for conversation analysis. Keep the audio, automatic draft and corrected version in an orderly version history.
Check quotations and retention
Before submission, compare each interview quotation in the results chapter with the recording and corrected transcript. Check pseudonyms in metadata, file names and appendices. Do not publish raw interview files merely because they exist in your research folder. Follow the authorised retention and deletion plan.
Explain the limits of automatic transcription and your correction strategy. The software produces a draft, not an authoritative record. A traceable review process protects participants and supports the credibility of your interpretation.
Final submission context
Formal details can feel like a separate writing task, but they matter just as much for a printed submission. Anything missing, misplaced or inconsistently formatted in the document will also appear in the bound copy.
Use this guide together with your cover page, table of contents, page numbers, source notes and appendices. Prepare the final PDF for printing and binding only after the complete file has been checked.
Practical check before PDF export
- Do headings, chapter structure and page numbers match?
- Are sources, figures and tables included completely?
- Are required elements such as declarations, appendices or the cover page included where required?
- Did you open and check the final PDF after exporting it?
Checklist
- Checked consent and approvals.
- Reviewed tool storage and access.
- Corrected transcript against audio.
- Verified quotes and pseudonyms.
Common mistakes
- Uploading raw recordings without a check.
- Treating output as exact.
- Leaving identifiers in appendices.
Prepare the finished thesis for submission
Once the content and university requirements are checked, review your PDF and the available printing and binding options.
Review printing optionsRelated content
Explore related guidance on thesis structure, sources, formatting and final submission.
Frequently asked questions
Can I use any AI service?
Follow your project approvals, university rules and applicable privacy requirements.
Do I need to replay the audio?
Yes, review systematically and focus especially on important claims.
Should I disclose the tool?
Follow department guidance and document its methodological role.