Authors : Soumdeep Dutta; Dr. K. Karthikayani

Volume/Issue : Volume 9 - 2024, Issue 10 - October

Google Scholar : https://tinyurl.com/58tnvjfw

Scribd : https://tinyurl.com/5e6ycb86

DOI : https://doi.org/10.38124/ijisrt/IJISRT24OCT122

Note : A published paper may take 4-5 working days from the publication date to appear in PlumX Metrics, Semantic Scholar, and ResearchGate.

Abstract : The rapid advancement of artificial intelligence has led to the development of more sophisticated chatbots capable of enhancing user interactions. This project presents a chatbot system that integrates speech recognition with traditional text input, enabling users to interact through both voice and text. Using NLP techniques such as tokenization, lemmatization, and part-of-speech tagging, the system effectively processes user inputs to match predefined intents stored in a JSON file. By integrating Google’s Speech-to-Text API, this chatbot dynamically processes voice commands, offering an improved, flexible user experience. The system is easily adaptable to various domains through the update of intents, providing a robust solution for dynamic, real-time conversational agents.

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