Language Agnostic Chatbot: Intelligent Multilingual Communication System
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Abstract
In today’s interconnected world, communication across multiple languages has become a fundamental requirement for digital systems. Traditional chatbot systems are typically designed for a single language or require separate models for each language, which limits their scalability and usability in multilingual environments. This research focuses on the design and development of a language-agnostic chatbot that can understand and respond to user queries in multiple languages without relying on language-specific implementations.
The proposed system integrates advanced techniques from Natural Language Processing (NLP), machine learning, and machine translation to create a unified framework for multilingual communication. The chatbot first detects the input language, translates it into a common processing language, and then uses an NLP-based model to interpret user intent and generate appropriate responses. The response is then translated back into the user’s original language, ensuring a seamless conversational experience.
The system is designed to be scalable, efficient, and adaptable across different domains such as customer support, education, healthcare, and e-commerce. Experimental evaluation demonstrates that the chatbot achieves high accuracy in intent recognition and maintains low response time across various languages. Additionally, the proposed approach significantly reduces development complexity compared to traditional multilingual chatbot systems.This research highlights the importance of language-independent AI systems and provides a practical solution for enhancing global accessibility and user interaction in intelligent conversational systems
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