Verbatim transcript workflow for confidential interviews.
Verbatim Transcript Solution turns long interview audio into a
timestamped, speaker-labeled transcript. The workflow preserves
conversational wording while preparing a structured Word
document that can be reviewed without manually rebuilding every
speaker turn.
Role
Workflow and AI system builder
Stack
Audio chunks, LLM, DOCX
Contribution
Pipeline, prompts, formatting, redaction
Outcome
Timestamped transcript
01
Started from messy interview audio
The source material came from participant conversations where
exact wording, speaker sequence, and timestamps mattered more
than a polished summary.
02
Split long files into reliable chunks
Audio is divided by time interval or silence detection so each
transcription request stays manageable and the final document
can be merged in the correct order.
03
Kept the output verbatim
The transcription prompt focuses on preserving filler words,
repeated phrases, speaker labels, and timestamp ranges instead
of rewriting the conversation into a cleaner narrative.
04
Prepared review-ready documents
Each chunk is normalized into a shared schema before the parts
are merged into one Word document for review, annotation, and
downstream analysis.
Confidential workflow
Public evidence without exposing private transcript data.
Due to NDA obligations and data compliance requirements, the
participant names and most transcript contents are intentionally
censored. The screenshots below are sanitized to show the document
format and pipeline, not the private interview details.
Sanitized transcript excerpt showing timestamp ranges, speaker labels, and redaction blocks for protected participant content.Open full-sizeOperational pipeline from audio import and chunking through LLM transcription, structured output, and DOCX export.Open full-size
Data handling
The portfolio version is intentionally censored.
The transcript includes participant speech and contextual
research details, so the public case study avoids displaying
names, personally identifying details, or long private
passages. The visible artifacts only demonstrate the workflow,
formatting, and output structure.
Transcription pipeline
From raw audio to one reviewed document.
Import audioLoad the source file and detect codec, duration, and sample rate.
Chunk audioSplit long recordings by silence or fixed intervals.
Select modelConfigure the transcription LLM, language, and credentials.
Transcribe chunksSend each segment to the API and collect raw transcript text.
Structure outputNormalize timestamps, speakers, sections, and chunk order.
Export DOCXMerge every chunk into one Word document for review.
