How to Transcribe Interviews for Qualitative Research

Qualitative researchers spend countless hours transcribing. AI transcription can reduce this dramatically while maintaining the accuracy your analysis requires.

Transcription in Research

Interview transcription isn't just converting speech to text—it's creating the data you'll analyze. Quality matters for coding, theme identification, and quotes.

Verbatim vs Clean Transcription

• Verbatim: Every um, pause, and repetition included
• Clean: Readable text, filler words removed
• For analysis: Clean is usually sufficient
• For discourse analysis: Verbatim may be required

IRB and Ethics

Research involving human subjects typically requires data protection. Check your IRB requirements. Local transcription often satisfies data security requirements that cloud services can't meet.

Workflow for Researchers

1. Record interview with participant consent
2. Transfer recording to secure local storage
3. Run through local AI transcription
4. Review and correct any errors
5. Anonymize as needed (names, locations)
6. Import into qualitative analysis software

Quality Control

• Spot-check random sections against audio
• Verify technical terms and proper nouns
• Note unclear sections rather than guessing
• Use timestamps for reference

Time Savings

Traditional transcription: 4-6 hours per hour of audio. AI transcription with review: 1-2 hours per hour of audio. For a 20-interview study, that's 60-80 hours saved.