ANGLIPS HUMAN INTERACTING CHABOT USING NLP AND DEEP LEARNING

Registration ID: IJNRD_227113

Published ID: IJNRD2408353

DOI: Click Here to Get

Ipsita Ankita Hota , Dr. Ranjan Kumar Dash

Deep-learning, Neural-network, Qt-designer, PyQt5, Speech-reorganization API.

Anglips is a human interacting deep-learning NLP and neural network-based Chabot. It includes GUI with the help of Pyqt5 and the Qt-designer tool. Chabot is like a good talkable friend for every introverted person. Here the Chabot is designed for human interaction with both speech and text-based. Initially, a GUI displays with two buttons START and EXIT buttons by pressing the START button it will start the application. Here a speech-reorganization API takes a vital role in human interaction, it takes the voice input of the user through the microphone and converts it into machine-understandable language during which it goes from listening to recognizing mode after which the system gives a corresponding response to the user. In the proposed method 100 intents were taken with more than 4 responses for training and testing with 21 intents and gives accuracy of 95.24% which makes it more accurate. Chatbots are useful for conversation as well as business, marketing, FAQ, and entertainment purposes. Anglips supports both speech and text-based conversation.

Published Paper   E-Certificate

Ipsita Ankita Hota & Dr. Ranjan Kumar Dash (August-2024). ANGLIPS HUMAN INTERACTING CHABOT USING NLP AND DEEP LEARNING. INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT, 9(8), d470-d481. https://ijnrd.org/papers/IJNRD2408353.pdf

Volume 9 Issue 8, August-2024

Pages : d470-d481

Paper Reg. ID: IJNRD_227113

Published Paper Id: IJNRD2408353

Downloads: 000122003

Research Area: Computer Science & Technology 

Country: Bhubaneswar, Odisha, India

Published Paper PDF: https://ijnrd.org/papers/IJNRD2408353.pdf

Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRD2408353

Journal Name: INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT(IJNRD)

ISSN: 2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar | ESTD YEAR: 2016

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