For journalists and qualitative researchers, recorded interviews are the raw material of the work. But between the recording and the publishable insight lies a painful bottleneck: transcription. A one-hour interview takes 4–6 hours to transcribe manually at professional speed. A researcher running 20 interviews faces 80–120 hours of transcription work before the real analysis can even begin.
AI transcription doesn't just speed this up — it transforms the entire post-interview workflow. Transcription time drops from hours to minutes. Summaries are generated automatically. Themes can be identified across multiple interviews with conversational queries. The bottleneck disappears.
Who This Is For
The AI-Enhanced Interview Workflow
Record the Interview
Use any recording setup — phone voice memo, Zoom/Teams recording, dedicated recorder. MP3, M4A, WAV, and most common formats are supported. For best accuracy, minimize background noise and use a directional mic if possible.
Upload and Transcribe
Upload the audio file to laminai. Whisper large-v3 transcribes the speech to text, handling accents, varied speaking speeds, and background noise gracefully. A 60-minute interview is typically ready in under 2 minutes.
Review the AI Summary
An AI-generated summary identifies the main themes, key points, and notable quotes from the interview. This gives you an immediate overview before diving into the full transcript — helping prioritize which sections deserve closer reading.
Query with AI Chat
Ask targeted questions: "What did the participant say about their biggest frustration?" "Find all mentions of budget constraints." "Summarize the participant's attitude toward remote work." AI searches the full transcript and returns precise answers.
Export and Analyze
Export the full transcript for coding in qualitative analysis tools, or use the AI's thematic summaries directly in your analysis. Cross-reference multiple interview transcripts for pattern identification.
Process each interview separately, then use the AI chat to ask thematic questions across all your transcripts. "What did participants consistently mention as barriers?" lets you do rapid cross-interview analysis that would take days manually.
Accuracy and Verification
AI transcription accuracy on clear interview audio typically exceeds 95–97% word error rate for standard English. For research and journalism use, this means:
- Always verify direct quotes against the original recording before publishing or citing them. AI may mishear proper nouns, technical terms, or domain-specific vocabulary.
- Proper nouns require attention — names of people, places, and organizations are most frequently mis-transcribed. Review these carefully.
- Accents and dialects — Whisper handles a wide range of accents well, but heavy regional dialects may have higher error rates. Flag and verify these sections.
- Overlapping speech — when two speakers talk simultaneously, accuracy drops significantly. Note these moments in the recording for manual review.
Never attribute a quote to a source based solely on the AI transcript without verifying it against the original recording. AI transcription is excellent for identifying where quotes occur and rapidly searching content, but direct attribution requires human verification of the exact words.
"AI transcription doesn't replace the researcher's judgment — it eliminates the mechanical work so judgment is all that's left."
Multilingual Interview Support
International researchers and journalists frequently work with recordings in multiple languages. Whisper supports transcription in 99+ languages, including Spanish, French, German, Mandarin, Japanese, Arabic, Hindi, Portuguese, Russian, and many more. For non-English interviews, laminai can transcribe in the original language and optionally translate to English for AI analysis.
Transcribe Your Interview Recordings
Upload any interview audio and get a full transcript + AI summary in minutes. Free to start.
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