Add Voice Recorder - Whisper transcription tool for Obsidian
Features: - Audio recording with pause/resume and visual feedback - Local Whisper transcription (tiny/base/small models) - 7 note types: instructions, capture, meeting, idea, daily, review, journal - Claude CLI integration for intelligent note processing - PKM context integration (reads vault files for better processing) - Auto-organization into type-specific folders - Daily notes with yesterday's task carryover - Language-adaptive responses (matches transcript language) - Custom icon and Windows desktop shortcut helpers Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
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# Whisper Voice Memo Transcription for Obsidian
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## Overview
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A simple, free, local transcription setup that:
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- Uses OpenAI Whisper (large-v3 model) for high-quality transcription
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- Handles French Canadian accent and English seamlessly
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- Auto-detects language switches mid-sentence
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- Outputs formatted markdown notes to Obsidian
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- Runs via conda environment `test_env`
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---
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## Configuration
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| Setting | Value |
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|---------|-------|
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| Conda Environment | `test_env` |
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| Output Directory | `C:\Users\antoi\antoine\My Libraries\Antoine Brain Extension\+\Transcripts` |
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| Model | `openai/whisper-large-v3` |
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| Supported Formats | mp3, m4a, wav, ogg, flac, webm |
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---
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## Installation
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### Step 1: Activate conda environment
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```bash
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conda activate test_env
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```
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### Step 2: Install insanely-fast-whisper
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```bash
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pip install insanely-fast-whisper
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```
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### Step 3: Verify installation
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```bash
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insanely-fast-whisper --help
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```
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---
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## Batch Script: Transcribe.bat
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Save this file to your Desktop or a convenient location.
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**File:** `Transcribe.bat`
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```batch
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@echo off
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setlocal enabledelayedexpansion
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:: ============================================
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:: CONFIGURATION - Edit these paths as needed
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:: ============================================
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set "OUTPUT_DIR=C:\Users\antoi\antoine\My Libraries\Antoine Brain Extension\+\Transcripts"
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set "CONDA_ENV=test_env"
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set "CONDA_PATH=C:\Users\antoi\anaconda3\Scripts\activate.bat"
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:: ============================================
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:: MAIN SCRIPT - No edits needed below
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:: ============================================
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:: Check if file was dragged onto script
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if "%~1"=="" (
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echo.
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echo ========================================
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echo Voice Memo Transcriber
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echo ========================================
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echo.
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echo Drag an audio file onto this script!
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echo Or paste the full path below:
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echo.
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set /p "AUDIO_FILE=File path: "
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) else (
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set "AUDIO_FILE=%~1"
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)
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:: Generate timestamp for filename
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for /f "tokens=1-5 delims=/:.- " %%a in ("%date% %time%") do (
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set "TIMESTAMP=%%c-%%a-%%b %%d-%%e"
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)
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set "NOTE_NAME=Voice Note %TIMESTAMP%.md"
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set "TEMP_FILE=%TEMP%\whisper_output.txt"
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echo.
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echo ========================================
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echo Transcribing: %AUDIO_FILE%
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echo Output: %NOTE_NAME%
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echo ========================================
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echo.
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echo This may take a few minutes for long recordings...
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echo.
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:: Activate conda environment and run whisper
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call %CONDA_PATH% %CONDA_ENV%
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insanely-fast-whisper --file-name "%AUDIO_FILE%" --transcript-path "%TEMP_FILE%" --model-name openai/whisper-large-v3
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:: Check if transcription succeeded
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if not exist "%TEMP_FILE%" (
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echo.
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echo ERROR: Transcription failed!
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echo Check that the audio file exists and is valid.
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echo.
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pause
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exit /b 1
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)
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:: Create markdown note with YAML frontmatter
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echo --- > "%OUTPUT_DIR%\%NOTE_NAME%"
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echo created: %date% %time:~0,5% >> "%OUTPUT_DIR%\%NOTE_NAME%"
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echo type: voice-note >> "%OUTPUT_DIR%\%NOTE_NAME%"
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echo status: raw >> "%OUTPUT_DIR%\%NOTE_NAME%"
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echo tags: >> "%OUTPUT_DIR%\%NOTE_NAME%"
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echo - transcript >> "%OUTPUT_DIR%\%NOTE_NAME%"
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echo - voice-memo >> "%OUTPUT_DIR%\%NOTE_NAME%"
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echo --- >> "%OUTPUT_DIR%\%NOTE_NAME%"
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echo. >> "%OUTPUT_DIR%\%NOTE_NAME%"
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echo # Voice Note - %date% at %time:~0,5% >> "%OUTPUT_DIR%\%NOTE_NAME%"
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echo. >> "%OUTPUT_DIR%\%NOTE_NAME%"
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echo ## Metadata >> "%OUTPUT_DIR%\%NOTE_NAME%"
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echo. >> "%OUTPUT_DIR%\%NOTE_NAME%"
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echo - **Source file:** `%~nx1` >> "%OUTPUT_DIR%\%NOTE_NAME%"
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echo - **Transcribed:** %date% %time:~0,5% >> "%OUTPUT_DIR%\%NOTE_NAME%"
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echo. >> "%OUTPUT_DIR%\%NOTE_NAME%"
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echo --- >> "%OUTPUT_DIR%\%NOTE_NAME%"
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echo. >> "%OUTPUT_DIR%\%NOTE_NAME%"
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echo ## Raw Transcript >> "%OUTPUT_DIR%\%NOTE_NAME%"
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echo. >> "%OUTPUT_DIR%\%NOTE_NAME%"
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type "%TEMP_FILE%" >> "%OUTPUT_DIR%\%NOTE_NAME%"
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echo. >> "%OUTPUT_DIR%\%NOTE_NAME%"
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echo. >> "%OUTPUT_DIR%\%NOTE_NAME%"
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echo --- >> "%OUTPUT_DIR%\%NOTE_NAME%"
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echo. >> "%OUTPUT_DIR%\%NOTE_NAME%"
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echo ## Notes distillees >> "%OUTPUT_DIR%\%NOTE_NAME%"
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echo. >> "%OUTPUT_DIR%\%NOTE_NAME%"
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echo ^<!-- Coller le transcript dans Claude pour organiser et distiller --^> >> "%OUTPUT_DIR%\%NOTE_NAME%"
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echo. >> "%OUTPUT_DIR%\%NOTE_NAME%"
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:: Cleanup temp file
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del "%TEMP_FILE%" 2>nul
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echo.
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echo ========================================
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echo DONE!
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echo Created: %NOTE_NAME%
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echo Location: %OUTPUT_DIR%
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echo ========================================
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echo.
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pause
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```
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---
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## Usage
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### Method 1: Drag and Drop
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1. Record your voice memo (any app)
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2. Drag the audio file onto `Transcribe.bat`
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3. Wait for transcription (few minutes for 30min audio)
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4. Find your note in Obsidian
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### Method 2: Double-click and Paste Path
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1. Double-click `Transcribe.bat`
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2. Paste the full path to your audio file
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3. Press Enter
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4. Wait for transcription
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---
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## Output Format
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Each transcription creates a markdown file like this:
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```markdown
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---
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created: 2026-01-15 14:30
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type: voice-note
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status: raw
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tags:
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- transcript
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- voice-memo
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---
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# Voice Note - 2026-01-15 at 14:30
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## Metadata
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- **Source file:** `recording.m4a`
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- **Transcribed:** 2026-01-15 14:30
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---
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## Raw Transcript
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[Your transcribed text appears here...]
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---
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## Notes distillees
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<!-- Coller le transcript dans Claude pour organiser et distiller -->
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```
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---
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## Processing with Claude
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After transcription, use this prompt template to organize your notes:
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```
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Voici un transcript de notes vocales en français/anglais.
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Peux-tu:
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1. Corriger les erreurs de transcription évidentes
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2. Organiser par thèmes/sujets
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3. Extraire les points clés et action items
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4. Reformatter en notes structurées
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Garde le contenu original mais rends-le plus lisible.
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---
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[COLLER LE TRANSCRIPT ICI]
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```
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---
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## Troubleshooting
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### "conda is not recognized"
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- Verify conda path: `where conda`
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- Update `CONDA_PATH` in the script to match your installation
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### Transcription takes too long
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- The `large-v3` model is accurate but slow on CPU
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- For faster (less accurate) results, change model to:
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```
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--model-name openai/whisper-medium
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```
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or
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```
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--model-name openai/whisper-small
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```
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### GPU acceleration
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If you have an NVIDIA GPU, install CUDA support:
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```bash
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pip install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cu118
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```
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### Wrong language detected
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Add language hint to the whisper command:
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```bash
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insanely-fast-whisper --file-name "audio.mp3" --transcript-path "output.txt" --model-name openai/whisper-large-v3 --language fr
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```
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---
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## Alternative: Python Script Version
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For more control or integration with other tools:
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**File:** `transcribe.py`
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```python
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import subprocess
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import sys
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from datetime import datetime
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from pathlib import Path
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# Configuration
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OUTPUT_DIR = Path(r"C:\Users\antoi\antoine\My Libraries\Antoine Brain Extension\+\Transcripts")
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MODEL = "openai/whisper-large-v3"
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def transcribe(audio_path: str):
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audio_file = Path(audio_path)
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timestamp = datetime.now().strftime("%Y-%m-%d %H-%M")
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note_name = f"Voice Note {timestamp}.md"
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temp_file = Path.home() / "AppData/Local/Temp/whisper_output.txt"
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print(f"\n🎙️ Transcribing: {audio_file.name}")
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print(f"📝 Output: {note_name}\n")
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# Run whisper
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subprocess.run([
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"insanely-fast-whisper",
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"--file-name", str(audio_file),
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"--transcript-path", str(temp_file),
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"--model-name", MODEL
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])
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# Read transcript
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transcript = temp_file.read_text(encoding="utf-8")
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# Create markdown note
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note_content = f"""---
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created: {datetime.now().strftime("%Y-%m-%d %H:%M")}
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type: voice-note
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status: raw
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tags:
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- transcript
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- voice-memo
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---
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# Voice Note - {datetime.now().strftime("%Y-%m-%d")} at {datetime.now().strftime("%H:%M")}
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## Metadata
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- **Source file:** `{audio_file.name}`
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- **Transcribed:** {datetime.now().strftime("%Y-%m-%d %H:%M")}
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---
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## Raw Transcript
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{transcript}
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---
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## Notes distillees
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<!-- Coller le transcript dans Claude pour organiser et distiller -->
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"""
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output_path = OUTPUT_DIR / note_name
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output_path.write_text(note_content, encoding="utf-8")
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print(f"\n✅ Done! Created: {note_name}")
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print(f"📁 Location: {OUTPUT_DIR}")
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if __name__ == "__main__":
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if len(sys.argv) > 1:
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transcribe(sys.argv[1])
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else:
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audio = input("Enter audio file path: ").strip('"')
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transcribe(audio)
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```
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Run with:
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```bash
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conda activate test_env
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python transcribe.py "path/to/audio.mp3"
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```
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---
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## Next Steps
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- [ ] Install `insanely-fast-whisper` in `test_env`
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- [ ] Save `Transcribe.bat` to Desktop
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- [ ] Test with a short audio clip
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- [ ] Pin to taskbar for quick access
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- [ ] Set up Claude prompt template for processing
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---
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## Resources
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- [insanely-fast-whisper GitHub](https://github.com/Vaibhavs10/insanely-fast-whisper)
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- [OpenAI Whisper](https://github.com/openai/whisper)
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- [Whisper model comparison](https://github.com/openai/whisper#available-models-and-languages)
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