1. Understand the workflow
Complete Transcribio guidelines: AI-assisted transcription review rules, clean verbatim standards, speaker label format, error correction priorities, and formatting requirements.
VideoText workflow guide
Transcribio Guidelines: Transcription Rules & Style Guide
Transcribio combines AI transcription with human review. This guide covers the formatting and review standards for Transcribio work — what to correct in AI output, speaker label format, and QA requirements.
Why teams use this workflow
- Transcribio Guidelines is part of the VideoText transcription, subtitle, and workflow toolkit.
- Each page focuses on a specific transcript, subtitle, formatting, or export task so teams can match the workflow to the outcome they need.
- Use the related workflows below to move from raw media to searchable text, captions, summaries, translations, or client-ready transcript formatting.
How it works
2. Use the matching VideoText tool
Follow the related links to transcript, subtitle, translation, formatting, or free utility flows that match the page intent.
3. Export a usable asset
Turn media, subtitles, or transcript text into an output that is ready for publishing, editing, accessibility, or team handoff.
Outputs you can use immediately
Workflow summary
Complete Transcribio guidelines: AI-assisted transcription review rules, clean verbatim standards, speaker label format, error correction priorities, and formatting requirements.
Related workflow handoffs
The page links to transcript, subtitle, translation, formatting, and export workflows that naturally fit the task.
Practical next steps
Start with the matching VideoText tool, review the output, then export the asset your creator, editor, client, or team needs.
Frequently asked questions
What is Transcribio's transcription model?
Transcribio uses an AI-plus-human workflow: AI generates an initial transcript, and human reviewers correct and refine the output. Reviewers focus on correcting AI errors (homophones, proper nouns, domain-specific terms) and cleaning filler words rather than transcribing from scratch.
What errors should I prioritize when reviewing Transcribio AI output?
Priority order for Transcribio AI review: (1) proper nouns and names — most commonly wrong; (2) homophones in context (their/there, to/too); (3) technical/domain terms; (4) filler word removal; (5) punctuation corrections; (6) speaker label verification. Start with high-impact errors and work down.
What speaker label format does Transcribio use?
Transcribio uses [Speaker N]: format — square brackets around the label, colon after closing bracket. Example: [Speaker 1]: The AI draft looks clean. [Speaker 2]: I spotted a few proper noun errors.
