Josh Knapp d00281f0c7 Fix critical integration issues for end-to-end functionality
- Rewrite SidecarManager as singleton with OnceLock, reusing one Python
  process across all commands instead of spawning per call
- Separate stdin/stdout ownership with dedicated BufReader to prevent
  data corruption between wait_for_ready and send_and_receive
- Add ensure_running() for auto-start on first command
- Fix asset protocol URL: use convertFileSrc() instead of manual
  encodeURIComponent which broke file paths with slashes
- Add +layout.svelte with global dark theme, CSS reset, and custom
  scrollbar styling to prevent white flash on startup
- Register AppState with Tauri .manage(), initialize SQLite database
  on app startup at ~/.voicetonotes/voice_to_notes.db
- Wire project commands (create/get/list) to real database queries
  instead of placeholder stubs

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
2026-02-26 16:50:14 -08:00

Voice to Notes

A desktop application that transcribes audio/video recordings with speaker identification, producing editable transcriptions with synchronized audio playback.

Goals

  • Speech-to-Text Transcription — Accurately convert spoken audio from recordings into text
  • Speaker Identification (Diarization) — Detect and distinguish between different speakers in a conversation
  • Speaker Naming — Assign and persist speaker names/IDs across the transcription
  • Synchronized Playback — Click any transcribed text segment to play back the corresponding audio for review and correction
  • Export Formats
    • Closed captioning files (SRT, VTT) for video
    • Plain text documents with speaker labels
  • AI Integration — Connect to AI providers to ask questions about the conversation and generate condensed notes/summaries

Platform Support

Platform Status
Linux Planned (initial target)
Windows Planned (initial target)
macOS Future (pending hardware)

Project Status

Early planning phase — Architecture and technology decisions in progress.

License

MIT

Description
Convert recorded audio to text with speaker identifying and text to audio scrubbing
Readme MIT 393 KiB
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