TranscribeNote: Local interview transcription proofing desk

A local tool that auto-labels speakers and makes fixing transcript errors painless for interviewers

Problem

People transcribing 1:1 interview recordings want low error rates and speaker identification, but existing tools either raise privacy concerns in the cloud or make proofreading inefficient with constant scrubbing back and forth.

Solution

Import audio in a browser or local app, run open-source models for speaker diarization and transcription to produce a timestamped transcript, then offer a side-by-side proofing interface where edits automatically stay in sync with the timeline; export to subtitles or documents.

Users

Journalists, user researchers, podcasters, and academic interviewers who handle one-on-one recordings

MVP

Import audio and transcribe locally; auto-separate Speaker 1/2; click-to-play and follow along with timestamps; quick typo fixes that preserve timecodes; export SRT/TXT/DOCX

Revenue

One-time purchase desktop app or monthly web subscription; free tier limits per-file length, pro unlocks batch processing and custom vocabulary

Why now

Open-source speech models are now good enough to run locally on ordinary laptops; privacy and pricing concerns with big-cloud transcription make niche users willing to pay for a dedicated tool