Update README.md

README.md

@@ -9,4 +9,148 @@ tags:
 - voicebased
 - ai
 - ml
----
+---
+
+
+# AuthEcho_Project
+
+This project contains well-trained deep learning models to predict the **Speaker** and their **Gender**.
+
+The repository offers a **Speaker and Gender Prediction System** built using **TensorFlow**, **Librosa**, and **Gradio**. The application predicts the top 3 speakers and their probabilities from an audio file, determines the speaker's gender, and classifies unknown speakers using a confidence threshold.
+
+## Features
+
+- Predicts the top 3 speakers from an audio file.
+- Determines the gender of the speaker.
+- Identifies unknown speakers with a confidence threshold.
+- Provides a Gradio interface for easy testing.
+
+## Getting Started
+
+### Prerequisites
+
+To run this application, you need:
+
+- **Python**: Version 3.8 or higher
+- Required Python libraries:
+  - `tensorflow`
+  - `numpy`
+  - `librosa`
+  - `gradio`
+  - `scikit-learn`
+
+Install the required libraries with:
+
+```
+pip install tensorflow numpy librosa gradio scikit-learn
+```
+
+### Installation
+
+1. **Clone the Repository**:
+
+```
+git clone https://github.com/your-username/speaker-gender-prediction.git
+cd speaker-gender-prediction
+```
+
+2. **Add Pre-Trained Models and Label Encoders**:
+
+Place the following files in the repository's root directory:
+- `lstm_speaker_model.h5`: Pre-trained speaker recognition model.
+- `lstm_gender_model.h5`: Pre-trained gender prediction model.
+- `lstm_speaker_label.pkl`: Label encoder for speaker classes.
+- `lstm_gender_label.pkl`: Label encoder for gender classes.
+
+### Usage
+
+Run the application using:
+
+```
+python app.py
+```
+
+### Gradio Interface
+
+The Gradio interface allows you to:
+
+- **Upload** an audio file or **record** audio directly.
+- Predict the **top 3 speakers** and their probabilities.
+- Determine the **gender** of the speaker.
+- Detect and classify **unknown speakers** using confidence thresholds.
+
+## Project Structure
+
+```
+.
+├── app.py                # Main application file
+├── models/lstm_speaker_model.h5   # Pre-trained speaker model (to be added)
+├── models/lstm_gender_model.h5    # Pre-trained gender model (to be added)
+├── models/lstm_speaker_label.pkl  # Speaker label encoder (to be added)
+├── models/lstm_gender_label.pkl   # Gender label encoder (to be added)
+├── requirements.txt        # Python dependencies
+└── README.md               # Project documentation
+```
+
+## Example Output
+
+### Top 3 Predicted Speakers:
+
+```
+The top 3 predicted speakers are:
+Speaker 1: 85.23%
+Speaker 2: 10.12%
+Speaker 3: 4.65%
+
+The predicted gender is: Male
+```
+
+### Unknown Speaker:
+
+```
+The top 3 predicted speakers are:
+Unknown: 45.23%
+
+The predicted gender is: Unknown
+```
+
+## How It Works
+
+1. **Feature Extraction**:
+   - Extracts **MFCCs**, **chroma features**, and **spectral contrast** from the input audio file using `librosa`.
+
+2. **Speaker and Gender Models**:
+   - **Speaker Model**: A pre-trained LSTM model classifies the speaker based on extracted features.
+   - **Gender Model**: A separate LSTM model determines the gender.
+
+3. **Unknown Detection**:
+   - If the highest confidence score for a speaker is below a defined threshold, the speaker is classified as "Unknown."
+
+## Roadmap
+
+- Add support for real-time audio predictions.
+- Improve unknown speaker detection using open-set recognition techniques.
+- Expand the dataset for more robust gender classification.
+
+## Contributing
+
+Contributions are welcome! To contribute:
+
+1. Fork the repository.
+2. Create a feature branch (`git checkout -b feature-branch-name`).
+3. Commit your changes (`git commit -m "Add new feature"`).
+4. Push to the branch (`git push origin feature-branch-name`).
+5. Open a Pull Request.
+
+## License
+
+This project is licensed under the **MIT License**. See the [LICENSE](LICENSE) file for details.
+
+
+
+
+## Acknowledgments
+
+- **TensorFlow**: For building the deep learning models.
+- **Librosa**: For audio processing and feature extraction.
+- **Gradio**: For creating the user interface.