Add WAV file support with MP3 conversion and reuse

- Add support for WAV files with automatic conversion to MP3
- Save converted MP3 files in the same directory as WAV files
- Reuse existing MP3 files if already converted
- Update documentation and requirements

README.md

@@ -1,10 +1,13 @@
 # mknotes
 
-A command-line tool to transcribe all MP3 and M4A audio files in a directory using Faster Whisper, then enhance the transcriptions into comprehensive notes using OpenAI's GPT-4.1 model.
+A command-line tool to transcribe all MP3, M4A, and WAV audio files in a directory using Faster Whisper, then enhance the transcriptions into comprehensive notes using OpenAI's GPT-4.1 model.
 
 ## Features
 
-- Batch transcribes all `.mp3` and `.m4a` files in a specified directory
+- Batch transcribes all `.mp3`, `.m4a`, and `.wav` files in a specified directory
+- Automatically converts WAV files to MP3 format before processing
+  - Converted MP3 files are saved in the same directory as the original WAV files
+  - Reuses existing MP3 files if they've already been converted
 - Saves transcriptions as `.txt` files
 - Enhances notes using GPT-4.1 with a custom prompt
 - Outputs enhanced notes in markdown format
@@ -23,6 +26,16 @@ source venv/bin/activate  # On Windows: venv\Scripts\activate
 
 # Install dependencies
 pip install -r requirements.txt
+
+# Install ffmpeg (required for WAV to MP3 conversion)
+# On Ubuntu/Debian:
+# sudo apt-get install ffmpeg
+
+# On macOS with Homebrew:
+# brew install ffmpeg
+
+# On Windows:
+# Download from https://ffmpeg.org/download.html and add to PATH
 ```
 
 ## Usage
@@ -32,7 +45,7 @@ export OPENAI_API_KEY="your-api-key-here"
 python main.py --input-dir /path/to/audio/files --output-dir /path/to/output [--turbo]
 ```
 
-- `--input-dir`: Directory containing audio files (required)
+- `--input-dir`: Directory containing audio files (.mp3, .m4a, .wav) (required)
 - `--output-dir`: Directory for output files (default: "output")
 - `--turbo`: Enable turbo mode for faster inference (uses int8_float16 compute type)
 - `--force`: Force re-processing of files even if output files already exist
@@ -62,3 +75,5 @@ If a compute type is not supported, the program will try the next one in the lis
 - Python 3.8+
 - [Faster Whisper](https://github.com/SYSTRAN/faster-whisper)
 - [OpenAI Python SDK](https://github.com/openai/openai-python)
+- [pydub](https://github.com/jiaaro/pydub) (for WAV to MP3 conversion)
+- [ffmpeg](https://ffmpeg.org/) (required by pydub for audio conversion)

enhancement_proposals.md

@@ -4,9 +4,10 @@ This document outlines proposed improvements for the mknotes software, grouped b
 
 ## Feature Enhancements
 
-- **Support for More Audio Formats**
+- **Support for More Audio Formats** ✅ (Partially implemented - WAV support added)
-  - Extend support beyond MP3 and M4A to include formats like WAV, FLAC, OGG, etc.
+  - ✅ Added support for WAV files with automatic conversion to MP3 before processing
-  - Update the `find_audio_files` function in `utils.py` to recognise additional extensions.
+  - Extend support to include additional formats like FLAC, OGG, etc.
+  - ✅ Updated the `find_audio_files` function in `utils.py` to recognize WAV extension
 
 - **Customizable Enhancement Prompts**
   - Allow users to provide their own prompts via CLI arguments or configuration files.

main.py

@@ -4,7 +4,7 @@ import os
 from tqdm import tqdm
 
 from src.cli import parse_args
-from src.utils import find_audio_files, ensure_directory_exists
+from src.utils import find_audio_files, ensure_directory_exists, convert_wav_to_mp3
 from src.transcriber import transcribe_audio
 from src.enhancer import enhance_note
 
@@ -39,9 +39,20 @@ def main():
             with open(txt_path, "r", encoding="utf-8") as f:
                 transcription = f.read()
         else:
+            # Convert WAV to MP3 if needed
+            path_to_transcribe = audio_path
+            
+            if audio_path.lower().endswith(".wav"):
+                print(f"Processing WAV file: {audio_path}")
+                mp3_path = convert_wav_to_mp3(audio_path)
+                if mp3_path:
+                    path_to_transcribe = mp3_path
+                else:
+                    print(f"Warning: Failed to convert {audio_path}. Will attempt to transcribe the WAV file directly.")
+            
             # Transcribe audio
             transcription = transcribe_audio(
-                audio_path,
+                path_to_transcribe,
                 txt_path,
                 model_size=model_size,
                 turbo=args.turbo

requirements.txt

@@ -2,3 +2,4 @@ faster-whisper
 openai
 argparse
 tqdm
+pydub

src/cli.py

@@ -10,7 +10,7 @@ def parse_args():
         "--input-dir",
         type=str,
         required=True,
-        help="Directory containing audio files (.mp3, .m4a)"
+        help="Directory containing audio files (.mp3, .m4a, .wav)"
     )
     parser.add_argument(
         "--output-dir",

src/utils.py

@@ -1,8 +1,10 @@
 # Helper functions for mknotes
 
 import os
+import tempfile
+from pydub import AudioSegment
 
-def find_audio_files(directory, extensions=(".mp3", ".m4a")):
+def find_audio_files(directory, extensions=(".mp3", ".m4a", ".wav")):
     """
     Recursively find all audio files in the given directory with the specified extensions.
     Returns a list of file paths.
@@ -19,3 +21,33 @@ def ensure_directory_exists(directory):
     Create the directory if it does not exist.
     """
     os.makedirs(directory, exist_ok=True)
+
+def convert_wav_to_mp3(wav_path):
+    """
+    Convert a WAV file to MP3 format using pydub if an MP3 version doesn't already exist.
+    Saves the MP3 file in the same directory as the WAV file.
+    
+    Args:
+        wav_path: Path to the WAV file
+        
+    Returns:
+        Path to the MP3 file
+    """
+    # Determine the output MP3 path (same directory, same name, different extension)
+    base_name = os.path.splitext(wav_path)[0]
+    mp3_path = base_name + ".mp3"
+    
+    # Check if MP3 version already exists
+    if os.path.exists(mp3_path):
+        print(f"Using existing MP3 file: {mp3_path}")
+        return mp3_path
+    
+    # Convert WAV to MP3
+    try:
+        audio = AudioSegment.from_wav(wav_path)
+        audio.export(mp3_path, format="mp3")
+        print(f"Converted {wav_path} to MP3 format at {mp3_path}")
+        return mp3_path
+    except Exception as e:
+        print(f"Error converting {wav_path} to MP3: {e}")
+        return None