Using TranscriptX¶

Short, outcome-focused walkthroughs for real jobs in the web UI. They complement the reference guides; they do not replace them.

Use the same sample transcript across the set so the story stays continuous: planning_review.json (synthetic three-speaker launch planning meeting).

Common workflows¶

Start here. First-time users should follow 1 → 5 in order.

#	Workflow	Outcome
1	First analysis	Import a transcript, run Balanced analysis, and read Overview
2	Identify and name speakers	Turn diarized labels into readable names before using speaker-level results (optional Apply auto-identify; USB: `inbox-watch --auto-name`)
3	Investigate with evidence	Answer a concrete question and trace it back to the transcript
4	Local AI synthesis	Use optional local AI for summary and meeting extracts
5	Export results	Package a finished run as a ZIP export with HTML (and EPUB when available)

Workflows 1–3 and 5 do not require local AI. Workflow 4 does.

Jump in when you need these tasks.

#	Workflow	Outcome
6	Explore Charts	Open run-scoped Charts for visual module outputs
7	Bundle into a group	Analyse several transcripts together
8	Correct while reading	Propose word/span fixes in Transcript Correct mode
9	Rename a transcript	Give a library transcript a clearer file name
10	Browse speaker profiles	Open speaker profiles linked across transcripts
11	Assist naming with voice	Enrol all + Pre-load so later transcripts propose people to confirm

TranscriptX web UI installed and running (Installation or Docker).
For workflow 4 only: local Ollama configured (LLM).
For workflow 10: at least one longitudinal profile (create via Speaker Identification), or follow the empty-state path in that guide.
For workflow 11: speaker_match extra, voice privacy enabled, seed named+linked profiles, and audio on managed transcripts.