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Built using Python, Streamlit, and NLTK, the Hate Speech Detection App employs a Decision Tree Classifier for identifying hate speech in text. It features real-time speech input, NLP preprocessing, and a user-friendly Streamlit interface, offering both visual and text-to-speech result presentation.

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hate-speech-detection

This Hate Speech Detection App is a project that leverages a Decision Tree Classifier to identify hate speech in text. Built using Python, Streamlit, and NLTK, the app preprocesses text data with Natural Language Processing (NLP) techniques, applies a bag-of-words representation using CountVectorizer, and trains a Decision Tree Classifier. Users can input text for hate speech detection through a Streamlit interface, which also supports real-time speech input.

Features:

  1. Hate speech detection using a Decision Tree Classifier
  2. NLP preprocessing for text data
  3. User-friendly Streamlit interface
  4. Visual and text-to-speech result presentation

Getting Started

  1. Clone the repository: "git clone https://github.com/your-username/hate-speech-detection-app.git"
  2. Install dependencies: "pip install -r requirements.txt"
  3. Run the app: "streamlit run app.py"

Usage

  1. Enter text in the provided input box.
  2. Click the "Detect Hate Speech" button.
  3. View the result visually and hear the text-to-speech output.

About

Built using Python, Streamlit, and NLTK, the Hate Speech Detection App employs a Decision Tree Classifier for identifying hate speech in text. It features real-time speech input, NLP preprocessing, and a user-friendly Streamlit interface, offering both visual and text-to-speech result presentation.

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