Speech Abuse Detector

1. Files Overview

• app.py:
  The main entry point of the application, handles the routing and runs the Flask server. It sets up the / route to serve the front-end interface and /process to handle the speech recognition and classification requests.

• detector.py:
  This file contains the SpeechAbuseDetector class, which encapsulates the logic for:

  • Capturing audio via microphone.
  • Converting audio to text using the SpeechRecognition library.
  • Using a pre-trained model from Hugging Face to classify text as "abusive" or "not abusive".

• templates/index.html:
  The HTML template for rendering the user interface. The user interacts with the app by clicking a button to start recording their voice.

• static/script.js:
  JavaScript logic to make a POST request to the server when the user clicks the button, sending the speech recognition result to the backend for classification.

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2. Dependencies

Before running the project, ensure you have the following dependencies installed:

pip install flask speechrecognition transformers torch

3. How to Run the Project

3.1 Setup

1. Install dependencies:
   First, install the necessary Python libraries by running the following command:

   pip install flask speechrecognition transformers torch
   

3.2 Running the Flask Application

1. Navigate to the project directory in your terminal.

2. Start the Flask application by running the following command:

   python app.py
   

3.Open your browser and go to: http://127.0.0.1:5000/