To Alleviate Depression by Interactive Artificial Conversation Entity

Authors

  • Uditesh Jha  Department of Computer Science and Engineering, Parul University, Limda, Gujarat, India
  • Keyur Khant  Department of Computer Science and Engineering, Parul University, Limda, Gujarat, India
  • Milan Kotadiya  Department of Computer Science and Engineering, Parul University, Limda, Gujarat, India
  • Kirti Gamdha  Department of Computer Science and Engineering, Parul University, Limda, Gujarat, India
  • Prof. Zalak Kansagra  Department of Computer Science and Engineering, Parul University, Limda, Gujarat, India

DOI:

https://doi.org//10.32628/CSEIT1952285

Keywords:

Depression, Chatbot, CBT, AIML, NLP

Abstract

This work is developed to alleviate depression. We provide transparency and privacy between user and chatbot by using the best approach which proves to be more reassuring, empathetic and non-judgmental. This new technology is interactive artificial conversation entity - chatbot. In this project, we are trying to relieve sufferer from depression. It is found that depression is the leading cause of disability globally. Projections indicates that after heart disease, depression is expected to become the second leading cause of disease burden by the year 2020. We will provide psychiatric treatment to users. After understanding the symptoms, causes and treatments of depression, user will be judged and treated according to defined and well-suited treatment. It will be helpful to those having depression, fear of sharing and fear of being judged. Also, it will help at those places where therapists are not easily available and to people who cannot afford therapist. A mobile application will be created for user interface.

References

  1. Katherine, D., 2001. Understanding Depression. Mind (National Association for Mental Health, 1(1).
  2. Moussavi, S., Chatterji, S., Verdes, E., Tandon, A., Patel, V. and Ustun, B., 2007. Depression, chronic diseases, and decrements in health: results from the World Health Surveys. The Lancet, 370(9590), pp.851-858.
  3. Ai, H., van Tol, M.J., Marsman, J.B.C., Veltman, D.J., Ruhé, H.G., van der Wee, N.J., Opmeer, E.M. and Aleman, A., 2018. Differential relations of suicidality in depression to brain activation during emotional and executive processing. Journal of psychiatric research, 105, pp.78-85.
  4. Ajilchi, B. and Nejati, V., 2017. Executive Functions in Students With Depression, Anxiety, and Stress Symptoms. Basic and clinical neuroscience, 8(3), p.223.
  5. Teasdale, J.D., 1985. Psychological treatments for depression: How do they work?. Behaviour Research and Therapy, 23(2), pp.157-165.
  6. Thies, I.M., Menon, N., Magapu, S., Subramony, M. and O’neill, J., 2017, September. How do you want your chatbot? An exploratory Wizard-of-Oz study with young, urban Indians. In IFIP Conference on Human-Computer Interaction (pp. 441-459). Springer, Cham.
  7. Jia, J., 2009. CSIEC: A computer assisted English learning chatbot based on textual knowledge and reasoning. Knowledge-Based Systems, 22(4), pp.249-255.
  8. Honghao, W., Yiwei, Z., Junjie, K., 2014. Building chatbot with Emotions. Journal of Stanford University, 23(1).
  9. Fitzpatrick, K.K., Darcy, A. and Vierhile, M., 2017. Delivering cognitive behavior therapy to young adults with symptoms of depression and anxiety using a fully automated conversational agent (Woebot): a randomized controlled trial. JMIR mental health, 4(2).
  10. AbuShawar, B. and Atwell, E., Automatic Extraction of Chatbot Training Data from Natural Dialogue Corpora. In RE-WOCHAT: Workshop on Collecting and Generating Resources for Chatbots and Conversational Agents-Development and Evaluation Workshop Programme (May 28 th, 2016) (p. 29).
  11. Huang, J., Zhou, M. and Yang, D., 2007, January. Extracting Chatbot Knowledge from Online Discussion Forums. In IJCAI(Vol. 7, pp. 423-428).
  12. Ramesh, K., Ravishankaran, S., Joshi, A. and Chandrasekaran, K., 2017, May. A survey of design techniques for conversational agents. In International Conference on Information, Communication and Computing Technology (pp. 336-350). Springer, Singapore.
  13. Dahiya, M., 2017. A tool of conversation: Chatbot. International Journal of Computer Sciences and Engineering, 5(5), pp.158-161.
  14. Shawar, B.A. and Atwell, E., 2003. Using dialogue corpora to train a chatbot. In Proceedings of the Corpus Linguistics 2003 conference (pp. 681-690).
  15. Hill, J., Ford, W.R. and Farreras, I.G., 2015. Real conversations with artificial intelligence: A comparison between human–human online conversations and human–chatbot conversations. Computers in Human Behavior, 49, pp.245-250.
  16. Tarun, L., Shreya, B., Shashank, B., Vasundhara, R., Ashish, P., 2018. Implementation of chatbot system using AI and NLP. International Journal of Inovative Research in Computer Science & Technology.
  17. Arsovski, S., Cheok, A.D., Idris, M. and Raffur, M.R.B.A., ANALYSIS OF THE CHATBOT OPEN SOURCE LANGUAGES AIML AND CHAT SCRIPT: A Review.
  18. Marietto, M.D.G.B., de Aguiar, R.V., Barbosa, G.D.O., Botelho, W.T., Pimentel, E., França, R.D.S. and da Silva, V.L., 2013. Artificial intelligence markup language: a brief tutorial. arXiv preprint arXiv:1307.3091.
  19. Ralph, W., Jaime, C., Barbara, G., Wendy, L., Mitchell, M., Raymond, P., Robert, W., 2010. White paper on Natural Language Processing. Association for Computational Linguistics.
  20. Weischedel, R., Carbonell, J., Grosz, B., Lehnert, W., Marcus, M., Perrault, R. and Wilensky, R., 1989, October. White paper on natural language processing. In Proceedings of the workshop on Speech and Natural Language (pp. 481-493). Association for Computational Linguistics.

Downloads

Published

2019-04-30

Issue

Section

Research Articles

How to Cite

[1]
Uditesh Jha, Keyur Khant, Milan Kotadiya, Kirti Gamdha, Prof. Zalak Kansagra, " To Alleviate Depression by Interactive Artificial Conversation Entity , IInternational Journal of Scientific Research in Computer Science, Engineering and Information Technology(IJSRCSEIT), ISSN : 2456-3307, Volume 5, Issue 2, pp.1039-1050, March-April-2019. Available at doi : https://doi.org/10.32628/CSEIT1952285