ChatSense – A Multilingual Chatbot

Authors

  • Saravana M K Department of Computer Science and Design, Dayananda Sagar Academy of Technology and Management, Bengaluru, Karnataka, India Author
  • Arman Mohammed Department of Computer Science and Design, Dayananda Sagar Academy of Technology and Management, Bengaluru, Karnataka, India Author
  • Sovan Pattanayak Department of Computer Science and Design, Dayananda Sagar Academy of Technology and Management, Bengaluru, Karnataka, India Author
  • Devendra Kumar Paswan Department of Computer Science and Design, Dayananda Sagar Academy of Technology and Management, Bengaluru, Karnataka, India Author
  • Yuvraj Dadhich Department of Computer Science and Design, Dayananda Sagar Academy of Technology and Management, Bengaluru, Karnataka, India Author

DOI:

https://doi.org/10.32628/IJSRST251222689

Keywords:

Multilingual Chatbots, Pre-Trained Language Models, Natural Language Processing, Knowledge Graphs, Machine Translation, Artificial Intelligence

Abstract

Multilingual chatbots have become essential tools for global communication, enabling seamless interaction across diverse languages and cultures. This paper presents the implementation of "ChatSense," a multilingual AI assistant leveraging pre-trained language models (PLMs) such as Gemini-2.0-flash, Google Translate APIs, and speech recognition technologies. The chatbot supports over 100 languages, addressing challenges like low- resource language support, contextual accuracy, and cultural adaptability. Our implementation integrates PLMs with knowledge graphs and fine-tuning strategies, including adapter-based tuning and prompt engineering, to enhance performance. Experimental results demonstrate significant improvements in response accuracy and user satisfaction across multiple languages, particularly in healthcare and educational domains. Graphical analyses illustrate the chatbot's effectiveness in handling cross-lingual queries and maintaining contextual coherence. This work contributes to advancing inclusive and efficient conversational AI systems.

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Published

28-04-2025

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Section

Research Articles