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.

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

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

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.