Update Readme

README.md

@@ -10,4 +10,89 @@ pinned: false
 short_description: This tool is intended to help transcribing interviews.
 ---
 
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+# Audio Transcription App
+
+A Gradio-based web application for transcribing audio files (MP3 or M4A) using OpenAI's Whisper model. Perfect for transcribing interviews and long audio recordings with features like silence removal and audio chunking.
+
+## Features
+
+- **Multiple Audio File Support**: Process multiple MP3 or M4A files simultaneously
+- **Silence Removal**: Option to remove silence from audio to reduce processing time and improve accuracy
+- **Audio Chunking**: Split long audio files into manageable chunks for better processing
+- **Multiple Language Support**: Supports German (de), English (en), French (fr), Spanish (es), and Italian (it)
+- **Multiple Whisper Models**: Choose from various Whisper model sizes (tiny to large-v3-turbo) based on your needs
+- **Detailed Output**: Get both full transcriptions and segment-wise transcriptions with timestamps
+- **Download Results**: All processed files and transcripts are provided in a convenient ZIP file
+
+## Setup
+
+1. Clone the repository
+2. Install the required dependencies:
+   ```bash
+   pip install -r requirements.txt
+   ```
+3. Make sure you have ffmpeg installed on your system
+
+## Usage
+
+1. Run the application:
+   ```bash
+   python app.py
+   ```
+2. Open the provided local URL in your web browser
+3. Upload your audio file(s)
+4. Configure the settings:
+   - Enable/disable silence removal
+   - Enable/disable audio chunking
+   - Select the Whisper model size
+   - Choose the target language
+5. Click "Process" to start transcription
+6. View the results and download the ZIP file containing all processed files
+
+## Settings
+
+### Silence Removal
+- **Minimum Silence Length**: 100-2000ms (default: 500ms)
+- **Silence Threshold**: -70 to -30dB (default: -50dB)
+
+### Chunking
+- **Chunk Duration**: 60-3600 seconds (default: 600 seconds/10 minutes)
+- **FFmpeg Path**: Path to ffmpeg executable (default: "ffmpeg")
+
+### Transcription
+- **Model Size**: Choose from tiny, base, small, medium, large, large-v2, large-v3, turbo, or large-v3-turbo
+- **Language**: German (de), English (en), French (fr), Spanish (es), Italian (it)
+
+## Output
+
+- **Full Transcription**: Complete text of the audio file
+- **Segmented Transcription**: Text segments with timestamps
+- **ZIP File**: Contains:
+  - Processed audio files
+  - Individual transcript files
+  - Combined transcript file
+
+## Deployment on Hugging Face Spaces
+
+1. Create a new Space on Hugging Face
+2. Choose "Gradio" as the SDK
+3. Upload the following files:
+   - app.py
+   - requirements.txt
+4. The app will automatically deploy and be available at your Space's URL
+
+## Requirements
+
+- Python 3.7+
+- ffmpeg
+- See requirements.txt for Python package dependencies
+
+## License
+
+This project is open source and available under the MIT License.
+
+## Acknowledgments
+
+- [OpenAI Whisper](https://github.com/openai/whisper)
+- [Gradio](https://gradio.app/)
+- [FFmpeg](https://ffmpeg.org/)