🧠 Offline Voice-Enabled NLP Chatbot for Smart Conversations
This project demonstrates a fully offline, voice-enabled chatbot that combines Natural Language Processing (NLP), speech recognition, and large language models (LLMs) to provide seamless and private AI conversations.

Built with privacy and performance in mind, the system runs entirely on local hardware, offering real-time interactions via both voice input and output, without relying on external APIs.

🚀 Key Features
🎙️ Voice Input + Output: Accepts voice commands and speaks responses aloud.

💡 GPT-style Intelligence: Uses a pre-downloaded LLM (OpenAI-compatible or other) for natural conversation generation.

🌐 Fully Offline Mode: No internet required after initial setup — ideal for privacy-sensitive environments.

🛠️ Modular Architecture: Cleanly separated modules for input, NLP processing, and output — easy to extend and adapt.

📦 Lightweight Deployment: Designed to run on mid-spec consumer hardware with Python and basic dependencies.

🔧 Tech Stack
Python, SpeechRecognition, pyttsx3 (TTS), transformers (Hugging Face), torch, FastAPI

Optional OpenAI/GPT-based logic (replaceable with local LLMs)

🧪 How It Works
User speaks → voice is transcribed to text using SpeechRecognition.

Text passed to NLP engine (e.g., GPT-2 or local model) to generate a response.

Response is spoken aloud using pyttsx3 for TTS.

A simple FastAPI interface is available for extended use.

📁 Repository
GitHub: https://github.com/AayushA10/nlp-chatbot

💡 Use Cases
Private personal assistant

Educational NLP demos

Edge AI devices

Conversational agent prototypes