🧠 CommAI – Communication Skill Analyzer (Django + NLP)

CommAI is an AI-powered web application that evaluates a user’s communication skills through both text and speech inputs, using Natural Language Processing (NLP) and a Django-based backend. The system analyzes a user’s response across multiple communication parameters and provides detailed, real-time feedback to help improve their communication effectiveness.

🔥 The project that blends AI, NLP, speech processing, and real-time feedback into a single intelligent platform.

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📌 Features

• 💬 Text Interface: Users can type messages to receive parameter-based feedback.
• 🎙️ Speech Interface: Users can record audio; the app converts it to text and analyzes it.
• 🧠 Seven NLP Parameters Analyzed:
  • Clarity
  • Conciseness
  • Tone & Sentiment
  • Engagement
  • Grammar & Spelling
  • Vocabulary Usage
  • Persuasiveness
• 🧾 Auto-generated feedback and level assessment: Poor, Intermediate, Excellent
• 🧊 Ollama integration for large language model-based evaluation (optional)
• 🖼️ Dynamic UI with JS interactivity + auto-disabling select tags
• 📦 Modular, scalable Django structure

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🛠️ Tech Stack

Component	Technology Used
Frontend	HTML5, CSS3, Bootstrap, JavaScript
Backend	Django (Python)
Speech Recognition	speech_recognition, pyaudio
NLP Processing	Python NLP libraries, Gemini API OpenAI whisper
Database	SQLite (Django default)
File Handling	Django static & media routing

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🚀 How to Run the Project

✅ Prerequisites

• Python 3.8+
• pip
• Git
• OpenAI Whisper (for speech to text conversion)
• Gemini API

📦 Install Required Packages

pip install -r requirements.txt

⚙️ Run the App Locally git clone https://github.com/YashKerkarTech04/commai-django-Yash.git cd commai-django-Yash python manage.py migrate python manage.py runserver

🧪 Usage Guide 💬 Text Evaluation Type your answer in the chat box Click Send Wait for backend to return parameter-wise analysis and level

🎤 Speech Evaluation Record your answer via microphone System converts to text and evaluates it similarly Results shown below the chat window

🌱 Future Enhancements User login and progress tracking Leaderboard for gamified skill improvement Multilingual support (Hindi, Marathi, etc.) Deployment to cloud (Render, Vercel, etc.) API-based analysis engine (Flask or FastAPI microservice)

pip install -r requirements.txt