Automated Transcript Editing for Content
Turning spoken word into polished, publication-ready written content with minimal human editing.
The Problem
Need to clean up raw transcripts (removing filler words, repeated words) to create clean articles or show notes.
Expected Outcome
Turning spoken word into polished, publication-ready written content with minimal human editing.
Tool Chain
Implementation Steps
- 1
Raw Audio Ingestion and ASR
Upload the raw audio. AssemblyAI provides a transcript with timestamps, filler words, and sentiment.
AssemblyAI - 2
Filler Word Removal
Filter the transcript to remove 'um', 'uh', repeated words, and false starts.
- 3
LLM Grammar and Punctuation Correction
Send the cleaned text to an LLM to correct grammar and ensure proper capitalization/punctuation for a final article.
- 4
Final Output and Publishing
Publish the final, cleaned transcript to a blog or documentation site.
Alternatives
World-class accuracy, but requires a separate step for filler word removal.
Cost Impact: N/A
Export Workflow
Coming SoonSoon you’ll export this stack to Zapier, n8n, or a starter repo with presets (env vars, webhooks, rate limits).