Emotion Detection Model

This repository contains the code and model for our Emotion Detection service, which predicts user emotions from audio input.

Table of Contents

• Description
• Deployment
• Contributing
• License

Description

Our Emotion Detection model uses machine learning to predict emotions from audio input. It's designed to help users analyze their emotional state and is integrated with our web application.

Deployment

We recommend deploying the model on Hugging Face's Model Hub. Here are the steps:

1. Upload Your Model:

   • Fork this repository and make your changes if necessary.
   • Commit your changes and push to your repository.
   • Go to the Hugging Face Model Hub and click "New Model."
   • Enter your repository's URL and details to create the model.

2. Create an Inference API:

   • Go to the "Inference API" tab in your Hugging Face account.
   • Configure the API with the relevant details (e.g., environment, GPU, CPU).
   • By now, you should have an ML endpoint that can be used in your front end.

3. Obtain an Authentication Token from Hugging Face:

   • To secure your model, get an authentication token from Hugging Face for your API. Refer to Hugging Face Authentication for details on how to obtain and use the token.

4. Usage from the Front End:

   • To use the API endpoint in your web application, refer to the front-end documentation: front-end-emotion-detection

Contributing

We welcome contributions and feedback from the community. If you find any issues or have suggestions, please open an issue or a pull request.

License

This project is licensed under the MIT License - see the LICENSE file for details.