Citation

Salhi I, El Guemmat K, Qbadou M, Mansouri K. Indones. J. Electr. Eng. Comput. Sci. 2021; 23(2): 1200-1211.

Copyright

(Copyright © 2021, Institute for Advanced Engineering and Science)

DOI

10.11591/ijeecs.v23.i2.pp1200-1211

PMID

unavailable

Abstract

Nowadays with COVID-19 ongoing epidemic outbreak, containment for weeks was one of the most effective measures adopted to deal with the spread of the virus until a vaccine could be efficient. Over that period, increased anxiety, depression, suicide attempts, and post-traumatic stress disorder are accumulated. Several studies referred to the need of using chatbots, which recognizes human emotions in such pandemic contexts. More recently, numerous research papers improved the ability of artificial intelligence methods to recognize human emotion. However, they are still limited. The aim of this paper is the development of a chatbot against the disturbing psychic consequences of the pandemic, taking human emotion recognition into account. The object is to help people; especially students; suffering from mental disorders, by progressively understanding the reasons behind them. This innovative chatbot was developed by using the natural language processing model of deep learning. An advanced model of deep learning has been elaborated the intention for people, and that to help them to regulate their mood and to reduce distortion of negative thoughts, that why a collection of a new database was done. The sequence-to-sequence model encoder and decoder consist of Long short-term memory cells, and it is defined with the bi-directional dynamic recurrent neural network packets. © 2021 Institute of Advanced Engineering and Science. All rights reserved.

Language: en

Keywords

COVID-19; Chatbot; LSTM; NLP; Psychic disorders; RNN; Sequence-to-sequence